Photovoltaic Hybrid Systems for Rural Electrification in the Mekong Countries 
 
 
 
 
 
 
 
 
 
A thesis submitted in partial fulfilment for the degree of Doctor of Engineering (Dr.-Ing) 
in the specialized area of Renewable Energy Technology at the Faculty of Electrical 
Engineering/Information Technology, University of Kassel. 
 
By 
 
M.Sc. Nipon Ketjoy 
 
 
 
 
 
Kassel:  Aug, 2005 
 
 
 
 
 
 
 
 
Supervisors: 
1. Prof. Dr.-Ing. Jürgen Schmid 
2. Prof. Dr. Wattanapong Rakwichian  
 iii
ERKLÄRUNG 
 
Hiermit versichere ich, dass ich die vorliegende Dissertation selbständig und ohne 
unerlaubte Hilfe angefertigt und andere als die in der Dissertation angegebenen 
Hilfsmittel nicht benutzt habe. Alle Stellen, die wörtlich oder sinngemäβ aus 
veröffentlichten oder unveröffentlichten Schriften entnommen sind, habe ich als 
solche kenntlich gemacht. Kein Teil dieser Arbeit ist in einem anderen Promotions- 
oder Habilitationsverfahren verwendet worden. 
 
 
 
Kassel, 24.08.2005
 iv 
ABSTRACT 
 
In rural areas of the Mekong Countries, the problem of electricity supplying rural 
communities is particularly alarming. Supplying power to these areas requires 
facilities that are not economically viable. However, government programs are under 
way to provide this product that is vital to community well being. A nation priority of 
Mekong Countries is to provide electrical power to people in rural areas, within 
normal budgetary constraints. Electricity must be introduced into rural areas in such a 
way that maximize the technical, economic and social benefit. Another consideration 
is the source of electrical generation and the effects on the natural environment. The 
main research purpose is to implement field tests, monitoring and evaluation of the 
PV-Diesel Hybrid System (PVHS) at the Energy Park of School of Renewable Energy 
Technology (SERT) in order to test the PVSH working under the meteorological 
conditions of the Mekong Countries and to develop a software simulation called RES, 
which studies the technical and economic performance of rural electrification options. 
This software must be easy to use and understand for the energy planner on rural 
electrification projects, to evaluate the technical and economic performance of the 
PVHS based on the renewable energy potential for rural electrification of the Mekong 
Country by using RES. Finally, this project aims to give guidance for the possible use 
of PVHS application in this region, particularly in regard to its technical and economic 
sustainability. PVHS should be promoted according to the principles of proper design 
and adequate follow up with maintenance, so that the number of satisfied users will 
be achieved. PVHS is not the only possible technology for rural electrification, but for 
the Mekong Countries it is one of the most proper choices. Other renewable energy 
options such as wind, biomass and hydro power need to be studied in future. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 v
ZUSAMMENFASSUNG 
 
In ländlichen Gebieten der Mekong-Länder stellt die Elektrifizierung abgelegener 
Dörfer und Gemeinden ein besonderes Problem dar. Die Energieversorgung dieser 
Gegenden erfordert Versorgungseinheiten, die häufig unter ökonomischen 
Gesichtspunkten nicht sinnvoll realisierbar sind. Allerdings wurden staatliche 
Förderungsprogramme initiiert, die den Aufbau von Energieversorgungsanlagen 
ermöglichen, die für den Wohlstand einer Region eine entscheidende Rolle spielen. 
Eines der Hauptziele der Mekong-Länder ist es, die ländliche Elektrifizierung im 
Rahmen normaler finanzieller Möglichkeiten durchzuführen. Die Einführung der 
Energieversorgung in den betreffenden Regionen muss in einer Weise durchgeführt 
werden, die einen maximalen Nutzen für die Gebiete in technischer, ökonomischer 
und sozialer Hinsicht bedeutet. Weiterhin ist die Wahl der Energiequelle und deren 
Einfluss auf die Umwelt zu bedenken. Der Schwerpunkt der vorliegenden 
Forschungsarbeit liegt in der Implementierung von Feldtests und der Überwachung 
und Auswertung des PV-Diesel-Hybridsystems (PVHS) im Energy Park der School of 
Renewable Energy Technology (SERT), um die Funktion des PVHS unter den 
klimatischen Bedingungen eines Mekong-Landes zu testen. Des weiteren wurde eine 
Simulationssoftware entwickelt, mit der Energieversorgungssysteme unter Nutzung 
erneuerbarer Energiequellen (RES) auf ihre ökonomische Eignung zur 
Elektrifizierung ländlicher Gebiete untersucht werden können. Diese Software muss 
einfach zu handhaben und für den Anlagenplaner leicht verständlich sein. Das PVHS 
wird im Hinblick auf die technische und ökonomische Leistungsfähigkeit unter dem 
Dargebot der Erneuerbaren Energiequellen in einem Mekong Land untersucht. Im 
Anschluss wird eine Anleitung für mögliche Anwendungen von PVHS in den 
genannten Regionen gegeben, insbesondere im Hinblick auf ihre technische und 
ökonomische Nachhaltigkeit. PVHS sollten vorangetrieben werden, indem sie 
angemessen ausgelegt und in der Folge in ausreichendem Maße für Wartung und 
Reparatur gesorgt ist. Nur dann können die Nutzer auf Dauer zufrieden gestellt 
werden. PVHS sind nicht die einzige Möglichkeit zur Elektrifizierung abgelegener 
Gebiete, aber für die Mekong-Länder stellen sie eine gute Wahl dar. Andere 
Optionen zur Nutzung Erneuerbarer Energien wie Wind, Biomasse und Wasserkraft 
sollten Gegenstand zukünftiger Forschung sein. 
 
 vi 
ACKNOWLEDGEMENTS 
 
I am very grateful to my supervisor Prof. Dr. -Ing. Jürgen Schmid for their guidance 
and encouragement of my research efforts. In addition, I would like to thank Prof. Dr. 
Wattanapong Rakwichian for his help with during this study.  
 
I am grateful to PD Dr. -Ing. Siegfried Heier from the Department of Electrical power 
supply systems that I also took an exciting course in Use of the Wind Energy. 
 
I would like to thank Dipl. -Ing. Franz Kininger from the Department of Efficient 
Energy Conversion for all great support during me study in the university. My very 
special thanks go to Ms. Claudia Erdt who assisted me on very many occasions. 
Thank to Dr. -Ing. Ingo Stadler and all Department staff for any kind support. 
 
I would like to thank Dipl. -Ing. Jiratkwin Rakwichian, Dipl. -Ing. Phongsuk Ampha, 
Mr. Arnusorn Saenparnjak, Dr. -Ing. Boonyang Plangklang, Mr. Amnoiy Ruengwaree 
and other Thai also German friends Dipl. -Ing. Thorsten Bülo, especially to Mr. Wolf 
Ruediger Engelke for providing great support to me during studying in Germany.  
 
Thanks to the Energy Conservation Promotion Fund (ENCON Fund), Energy Policy 
and Planning Office (EPPO), Ministry of Energy, Thailand (Fiscal Year 2003 budget)  
and Faculty of Science, Naresuan University for the financial support during my 
study. In addition, the thesis work was sponsored by National Research Council of 
Thailand (NRCT), a cooperated research by School of Renewable Energy 
Technology, Naresuan University, Thailand and a Department of Efficient Energy 
Conversion, University of Kassel, Germany. And thanks to the European 
Commission for give a change to joint in project Mini-Grid Kit NNE5-1999-00487 as I 
took a part of this project to my research. 
 
Thank to the Council on Renewable Energy in the Mekong Region (CORE) secretary 
office for provide me the information of Mekong Region. 
   
Finally, I would like to thank my family and parents, for their support during this time. 
 
 vii
TABLE OF CONTENTS 
1 INTRODUCTION………..………………………………………………………………1 
1.1 Motivation ....................................................................................................... 1 
1.2 Hybrid system technology............................................................................... 2 
1.3 Software simulations....................................................................................... 3 
1.4 Objectives of study ......................................................................................... 3 
1.5 Outline of the thesis ........................................................................................ 5 
2 RURAL ELECTRIFICATION IN THE MEKONG COUNTRY………..……………..7 
2.1 Introduction to Mekong Country...................................................................... 7 
 
2.1.1 Geography and demography .................................................................... 7 
 
2.1.2 Climate condition .................................................................................... 10 
 
2.1.3 Economic situation.................................................................................. 11 
2.2 Rural electrification situations ....................................................................... 14 
 
2.2.1 Rural electricity needs and development ................................................ 14 
 
2.2.2 General characteristic of rural energy use .............................................. 14 
 
2.2.3 Rural electrification ................................................................................. 16 
2.3 Rural electrification policy in selected Mekong Countries ............................ 18 
3 RENEWABLE HYBRID POWER SYSTEM………………….……………………..23 
3.1 Renewable energy potential in Mekong Country .......................................... 23 
 
3.1.1 Hydro energy .......................................................................................... 23 
 
3.1.2 Biomass energy ...................................................................................... 25 
 
3.1.3 Wind power............................................................................................. 27 
 
3.1.4 Solar energy ........................................................................................... 29 
3.2 PV hybrid system technology category......................................................... 30 
3.3 Prototype of hybrid system for Mekong Country........................................... 33 
 
3.3.1 Modular Systems Technology (MST)...................................................... 33 
 
3.3.2 Classes of power units............................................................................ 35 
 
3.3.3 The prototype system at SERT............................................................... 35 
3.4 Testing and monitoring of the prototype ....................................................... 36 
 
3.4.1 Test method............................................................................................ 36 
 
 viii 
3.4.2 Data monitoring system .......................................................................... 39 
 
3.4.3 Data analysis .......................................................................................... 41 
 
3.4.4 Technical performance evaluation results .............................................. 43 
4 RURAL ELECTRIFICATION SOFTWARE…….…………...………………………45 
4.1 Software concept ......................................................................................... 45 
4.2 Model and algorithm ..................................................................................... 46 
 
4.2.1 Solar radiation model.............................................................................. 47 
 
4.2.2 System component model ...................................................................... 50 
 
4.2.3 Economical model .................................................................................. 57 
4.3 Software testing............................................................................................ 61 
 
4.3.1 Validation of RES PVHS model compared with PVHS monitored ………61 
 
4.3.2 Validation of RES PVS model compared with PVS monitored ............... 63 
4.4 Summary ...................................................................................................... 66 
5 CASE STUDY OF RURAL ELECTRIFICATION IN MEKONG COUNTRIES.....67 
5.1 Introduction................................................................................................... 67 
5.2 Case of Ban Pang Praratchatang, Thailand .................................................. 67 
 
5.2.1 Description of Ban Pang Praratchatan .................................................... 67 
5.2.2 Input of RES ........................................................................................... 71 
5.2.3 System performance results of PVHS at Ban Pang Praratchatan ........... 72 
5.2.4 Economics performance results of PVHS at Ban Pang Praratchatan...... 75 
5.3 Case of Samaki, Cambodia .......................................................................... 76 
 
5.3.1 Description of Samaki............................................................................. 76 
5.3.2 Input of RES ........................................................................................... 78 
5.3.3 System performance results of PVHS at Samaki.................................... 78 
5.3.4 Economics performance results of PVHS at Samaki .............................. 81 
5.4 Case of Thapene, Lao PDR.......................................................................... 82 
 
5.4.1 Description of Thapene........................................................................... 82 
5.4.2 Input of RES ........................................................................................... 85 
5.4.3 System performance results of PVHS at BTP ........................................ 85 
5.4.4 Economics performance results of PVHS at BTP................................... 88 
5.5 Summary and outlook................................................................................... 89 
 ix
6 CONCLUSIONS AND RECOMMENDATIONS………………………………….…91 
6.1 Outlook and future work................................................................................ 92 
7 REFERENCES………………………………………………………………………...95 
8 APPENDICES………………………………………………………………………...101 
8.1 Appendix A: The hybrid system prototype drawing..................................... 101 
8.2 Appendix B: The algorithms and user interface of RES.............................. 111 
 x 
TABLE OF FIGURES 
 
Figure 2-1: Map of Mekong Countries ....................................................................... 8 
Figure 2-2: Mekong Countries population projection ................................................. 9 
Figure 2-3: Urban population projection..................................................................... 9 
Figure 2-4: Solar radiation on horizontal surface of Thailand................................... 10 
Figure 2-5: Solar radiation on horizontal surface of Cambodia ................................ 11 
Figure 2-6: The average solar radiation in typical region of Vietnam....................... 11 
Figure 2-7: Selected Mekong Country Gross Nation Product during 1997-2005 ..... 12 
Figure 2-8: Combinations of rural energy source in use in rural Laos...................... 16 
Figure 2-9: Rural energy in Pursat province, Cambodia .......................................... 16 
Figure 3-1: Series PV-diesel generator hybrid system............................................. 31 
Figure 3-2: Switched PV-diesel generator hybrid system ........................................ 32 
Figure 3-3: Parallel PV-diesel generator hybrid system........................................... 33 
Figure 3-4: Single and three phase AC-couple modular expandable hybrid............ 34 
Figure 3-5: Hybrid system prototype at SERT ......................................................... 36 
Figure 3-6: PVHS performance testing procedure with different loads profile ......... 37 
Figure 3-7: Load profile of small villages in northern of Thailand............................. 37 
Figure 3-8: Load profile of a single village in Chiangria, Thailand............................ 38 
Figure 3-9: Load profile of a Ban Pang Praratchatan village, Thailand.................... 38 
Figure 3-10: Load profile of a single household in Thailand .................................... 39 
Figure 3-11: Hourly of load in Luo Buo Tai Zi, Xinjiang, China ................................ 39 
Figure 3-12: Data monitoring system....................................................................... 40 
Figure 3-13: Correlation of energy consumption and energy produced by genset... 43 
Figure 3-14: Balance of energy of the PVHS at SERT ............................................ 44 
Figure 4-1: Structure of the RES.............................................................................. 46 
Figure 4-2: Comparison of titled solar radiation calculated by RES and monitored . 62 
Figure 4-3: Comparison of PV energy production calculated and monitored........... 63 
Figure 4-4: Comparison of genset energy production calculated and monitored......... 63 
Figure 4-5: PV system at Chiangria Province, Thailand .......................................... 64 
Figure 4-6: Comparison of titled solar radiation calculated and monitored.................. 65 
Figure 4-7: Comparison of PV energy production calculated and monitored ................ 65 
Figure 5-1: Map of Thailand and location of BPP in Chiang Rai province ............... 68 
Figure 5-2: Map of BPP village ................................................................................ 69 
Figure 5-3: Weekly demand profile of BPP village generate by RES....................... 70 
 xi
Figure 5-4 : Correlation of daily energy demand and energy produced by diesel .... 72 
Figure 5-5: Energy balance of the PVHS at BPP..................................................... 73 
Figure 5-6: System performance of the PVHS at BPP ............................................ 73 
Figure 5-7: Selected weekly power supply by PV, battery and battery SOC............ 74 
Figure 5-8: LCC analysis of different assumption .................................................... 75 
Figure 5-9 : Map of Cambodia, PV system installed and location of Samaki ........... 77 
Figure 5-10: Weekly demand profile of Samaki village generate by RES................ 78 
Figure 5-11: Correlation of daily energy demand and energy produced by diesel ... 79 
Figure 5-12: Energy balance of the PVHS at Samaki .............................................. 79 
Figure 5-13: System performance of the PVHS at Samaki ...................................... 80 
Figure 5-14: Weekly power supply by PV, battery and battery SOC of the PVHS... 80 
Figure 5-15: LCC analysis of different assumption of Samaki ................................. 82 
Figure 5-16: Map of Laos, location of Thapene Village in Loungphrabang.............. 83 
Figure 5-17: Daily load profile of Thapene village by SERT observation ................. 84 
Figure 5-18: Weekly load demand profile of Thapene village generate by RES...... 84 
Figure 5-19: Correlation of daily energy demand and energy produced by diesel ... 85 
Figure 5-20: Energy balance of the PVHS at Thapene............................................ 86 
Figure 5-21: System performance of the PVHS at Thapene.................................... 86 
Figure 5-22: Distribution weekly power supply by PV, battery and battery SOC...... 87 
Figure 5-23: Thapene LCC analysis of different assumption ................................... 88 
Figure 5-24: Levelized costs for PVHS, PVS, DGS and GE in selected countries .......... 90 
Figure 8-1: PVHS grid tried algorithm .................................................................... 111 
Figure 8-2: PVHS grid forming algorithm ............................................................... 112 
Figure 8-3: PVS algorithm...................................................................................... 113 
Figure 8-4: SHS algorithm ..................................................................................... 114 
Figure 8-5: BCS algorithm ..................................................................................... 115 
Figure 8-6: DGS (left) and GE (right) algorithm ..................................................... 116 
Figure 8-7: Main input user interface of PVHS....................................................... 117 
Figure 8-8: Example of Input data of PV panel, inverter and battery inverter......... 117 
Figure 8-9: Solar radiation input user interface ...................................................... 118 
Figure 8-10: Load input user interface ................................................................... 118 
Figure 8-11: System parameter result interface..................................................... 119 
Figure 8-12: Energy consumption result interface ................................................. 119 
Figure 8-13: Balance of energy result interface ..................................................... 119 
 xii 
Figure 8-14: System performance result interface ................................................. 120 
Figure 8-15: Economics result interface ................................................................ 120 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 xiii
TABLE OF TABLES 
 
Table 2-1: Sector contribution to real GDP and growth rate per capita in 2000 ............... 13 
Table 2-2: Estimates of rural household access to electricity................................... 17 
Table 2-3: Summary of the overall strategic planning, target and goals for EDC..... 19 
Table 3-1: PVHS performance ................................................................................. 44 
Table 4-1: Recommended Average Days for Months and Values of n..................... 47 
Table 4-2: Nominal and Standard conditions ........................................................... 52 
Table 4-3: Comparison of RES PVHS calculation and SERT PVHS monitored....... 62 
Table 4-4: Comparison of RES PVS calculation and Chiangria PVS monitored ...... 64 
Table 5-1: Renewable energy resource in BPP ....................................................... 69 
Table 5-2: Load demand and duration time of used in BPP..................................... 70 
Table 5-3: Comparison of the difference assumption of the PVHS economics……..75 
Table 5-4: Solar energy resource in Samaki ............................................................ 77 
Table 5-5: Comparison of the difference assumption of the PVHS economics ........ 81 
Table 5-6: BTP comparison of the difference assumption of the PVHS economics . 88 
Table 8-1: Components list .................................................................................... 101 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 xiv 
ABBREVATIONS 
 
ADB: Asian Development Bank 
BPP: Ban Pang Praratchatang 
BCS: Centralized PV Battery Charging Station  
CORE: Council on Renewable Energy in the Mekong Region 
CRO: Central Research Organization 
DEDP: Department of Energy Development and Promotion of Thailand 
DGS: Stand-Alone Diesel Generator Station  
ENCON Fund: Energy Conservation Promotion Fund  
EDC: Electricité du Cambodge 
EPPO: Energy Policy and Planning Office 
EVN: Electricity of Vietnam 
FAO: Food and Agriculture Organization 
GDP: Gross Domestic Production 
GE: Grid Extension  
GMS: Greater Mekong Subregion 
IEPF: Energy Institute of Francophonic Countries 
ISET: Institut für Solare Energieversorgungstechnik 
KTOE: Kilo Tones Oil Equipvalent 
MGCT: A Study of Mini – Grid Concept for the Villages without Electricity in Thailand 
MIME: Ministry of Industry, Mines and Energy  
MST: Modular Systems Technology 
MTOE: Million Tones Oil Equipvalent 
NGO: Non Government Organization 
NRCT: National Research Council of Thailand 
PEA: Provincial Electricity Authority of Thailand 
PV: Photovoltaic 
PVHS: PV-Diesel Hybrid System 
PVS: Stand-Alone PV Station  
PWD: Public Work Division  
RES: Rural Electrification System  
RWEDP: Regional Wood Energy Development Programme 
SB: Sunny Boy  
SBC: Sunny Boy Control  
 xv
SERT: School of Renewable Energy Technology 
SHS: Solar Home System 
SI: Sunny Island  
STEA: Science Technology and Environment Agency 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 xvi 
 
 1
1 INTRODUCTION 
 
1.1 Motivation 
 
Approximately 200 million people of the Mekong Country population live in rural 
areas. From that number only 10% in Cambodia, Lao PDR, Myanmar and Vietnam 
have access to the electric grid. The government of the Mekong Countries has a very 
strong policy to provide electricity to people in those areas. However, there are many 
problems in the implementation process such as financial, unclear planning and lack 
of proper technology. Almost all rural electrification projects are concentrating on 
conventional ways such as grid extension. This technology is sometimes not proper 
in some locations for example in Lao PDR and Myanmar, where almost all land areas 
are still covered by abundant forest. Grid extension may be a cause of environment 
effect and not economical enough because not many people actually live in that area.   
 
Mekong Country has very rich potential of renewable energy. This potential can be 
developed for rural electrification projects. Renewable energy is wide spread in this 
region and can be found at all locations. It should be considered for power generation 
sources because many technologies in this time can convert it into electrical energy 
such as photovoltaic (PV) generator, wind turbine, hydro generator and biomass 
conversion technology. One solution for rural electrification in this region is suitable 
by selecting the proper renewable energy conversion technology.        
 
In this study the focus is photovoltaic generator technology. Long experience has 
shown this technology is a one of the most efficient for rural electrification. However, 
many limitations of photovoltaics still exist, such as reliability when compared with 
diesel generator. But the diesel generator also has many disadvantages. Therefore 
the combination between the advantages of photovoltaic and diesel generator is one 
suitable solution for rural electrification technology of the Mekong Country. 
 
The photovoltaic hybrid system is a new technology for this region. There is not much 
technical experience for application in rural area. No data indicates this technology is 
suitable for rural areas of this region and it is quite difficult to use the experience from 
other regions to identify. Mekong region has specific conditions that are different with 
other regions. Therefore this study concentrates on the suitability and guideline of 
 2 
use of the photovoltaic hybrid system for rural electrification in Mekong region by 
studying the technical and economic performance to get exact data for suitable 
technology selection and suitable guideline for rural electrification in this region. 
 
1.2 Hybrid system technology  
 
Through the combination of renewable energy conversion technology devices, such 
as photovoltaic, wind turbine or hydro generators, with combustion generator and 
battery storage, it is possible to generate electricity in rural or remote areas 
competitively. Such systems are defined as hybrid energy systems and are used to 
provide electricity to rural village in developing countries. The combination of 
renewable and conventional energy technology compares favorably in both technical 
and economical performance with fossil fuel based and conventional grid rural area 
power supplies. [Wichert, et al, 1999] 
 
Applications of hybrid energy systems range from small power supplies for rural 
households, providing electricity for lighting, radio and other electrical appliance, to 
rural electrification for rural communities. Hybrid system technologies have 
advantages over conventional, combustion generator only in rural area power 
supplies where the load demand over the day is highly variable. A study of systems 
installed in the USA concludes that hybrid systems are cost-competitive with 
conventional systems where the ratio of heavy to light loads exceeds 3:1 [Markvart, 
2000]. If the load variability is less pronounced then other constraints, such as limited 
access or restricted environmental impact, may favor the application of renewable 
energy technology for rural area power supplies. Many experiences have shown that 
conventional combustion generator systems are often not suitable enough to respond 
to charging load demands varying operating conditions. 
 
In this study the AC-couple modular expandable hybrid system concept from the 
Institut für Solare Energieversorgungstechnik (ISET) is considered. The main 
components consist of photovoltaic generator, diesel genset, battery storage and 
power conversion device for the scope of the work. Other renewable energy 
technology such as wind turbine and hydro generator are not considered for this 
study.     
 3
1.3 Software simulations 
 
One of the most important goals of this research is to evaluate the technical and 
economic performance of the utilization of AC-couple PV hybrid system concept in 
the rural area of the Mekong Countries. It is impossible to make the experiment in 
several real sites because of time consumption and high budget need. Computer 
simulation is a time saving and cost-effective method that can be used for system 
design, performance evaluation, optimization and control strategy before a system is 
installed [Cherus, 2004]. With this way, the behaviour of real systems can be 
relatively accurately predicted and modified accordingly before implementation. In 
this study, system static behaviour is of particular interest. 
 
A wide variety of simulation tools, ranging from simple rules of thumb to sophisticated 
software packages, exist for the analysis and dimensioning of stand-alone 
photovoltaic systems. System designers and installers use the simple tools for sizing. 
Scientists and engineers typically use more involved simulation tools for optimization 
[Turcotte, 2001]. PV hybrid system software simulators on the market are designed 
with different goals in mind, and have various limitations for solving certain problems. 
Software tools related to photovoltaic hybrid systems can be classified into two 
categories:  static and dynamic models. Static simulators are used primarily for long-
term system performance predictions, economical analysis and component sizing, 
etc. Examples are, for instance, Hybrid Designer, Hybrid2, INSEL, PV-DesignPro-S, 
PVS, PVSYST and SOLSIM, which are generally considered suitable for system 
dimensioning and economic calculations for PV systems over a long-term period, 
usually annually. Dynamic system simulators give a closer look at system operation 
and enables study of power management and control strategies. They are able to 
simulate real system behaviour, but require special simulation environments to do 
this [Cherus, 2004]. In this study static system simulation of AC-couple modular 
expandable hybrid system concept is developed. 
 
1.4 Objectives of study 
 
Many people in rural area of Mekong Countries still lack electricity service. Many 
rural electrification projects in this region are through the government agencies and 
funding come from both government and donor agencies. Experience shows, almost 
all of those project failures are mainly caused by technical, economic evaluation and 
 4 
project management problems. This research concentrates on the technical and 
economic evaluation view. For technical problems, improper technology selection, 
design and component selection are main causes. For economic evaluation, lack of 
economic evaluation of the projects before starting is main cause.  
 
This research needs to study the proper option for rural electrification of Mekong 
Countries. By offering the PV Hybrid System, which an AC-couple modular 
expandable component concept of ISET is a choice for this region. Another 
concept is not considered in this work. The technical and economic performance 
from the actual site and from the software simulation need for confirms this proposes. 
Four specific objectives are proposed. 
 
• Implementation of field tests, monitoring and evaluation of the PVHS at 
Energy Park of School of Renewable Energy Technology (SERT) in order to 
test the PVSH working under the metrological conditions of the Mekong 
Country,   
• To develop a software simulation, which studies the technical and economic 
performance of rural electrification options. This software must be easy to use 
and understand for the energy planner on rural electrification projects,  
• To evaluate the technical and economic performance of the PV Hybrid 
System (PVHS) base on renewable energy potentials for rural electrification 
of Mekong Country by using the developed software,  
• To give guidance for the possible use of PVHS application in this region, 
particularly in regard to its technical and economic sustainability. 
 
In this thesis, the law data of Mekong Countries is provided by the Council on 
Renewable Energy in the Mekong Region (CORE) secretary office. The technical 
data of the PVHS is base on the prototype at the Energy Park of School of 
Renewable Energy Technology (SERT) and at DeMoTec of University of Kassel, 
which is installed under the EU project “Mini-Grid Kit”. 
 
 
 
 
 5
1.5 Outline of the thesis 
 
Chapter 1 gives an introduction to the concept of hybrid system technology, the need 
for simulation software tools, and objectives of study. Chapter 2 gives an introduction 
to Mekong Country, rural electrification situations of this region, such as geography 
and demography, climate conditions, economic situation and rural electrification 
policy. Chapter 3 presents the renewable energy potential in Mekong Country, PV 
hybrid system technology category, prototype of hybrid system for Mekong Country 
and testing and monitoring of the prototype. Chapter 4 presents a software concept, 
model, algorithm and testing. Chapter 5 presents the different case study from selected 
Mekong Country, system and economics performance analysis. Conclusions and 
recommendations are in Chapter 6, references are given in Chapter 7, and the 
appendix is in Chapter 8. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 6 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 7
2 RURAL ELECTRIFICATION IN THE MEKONG COUNTRY 
 
2.1 Introduction to Mekong Country 
 
The Mekong Countries is includes of six countries: The Kingdom of Cambodia, 
Yunnan province of People’s Republic China, Lao PDR, The union of Myanmar, The 
Kingdom of Thailand and the Socialist Republic of Vietnam. It is a vast area that 
possesses an enormous wealth and variety of natural resources, including a rich 
agricultural base, timber and fisheries, minerals and energy in the form of 
hydropower, coal and petroleum reserves. These resources fuel economic 
development and support rural livelihoods in an interrelated fashion. 
 
The great majority of these people live in rural areas where they lead subsistence or 
semi-subsistence agricultural lifestyles. Since the onset of peace in the 1990s, the 
peoples of the Mekong are experiencing rapid changes and improvements in their 
living standards and conditions. The Mekong countries are gradually shifting from 
subsistence farming to more diversified economies, and to more open, market-based 
systems. In parallel is the growing establishment of commercial relations among the 
six Mekong countries, notably in terms of cross-border trade, investment and labor 
mobility. 
 
The rich human and natural resource endowments of the Mekong region have made 
it a new frontier of Asian economic growth. Indeed, the Mekong region has the 
potential to be one of the world’s fastest growing areas. The Mekong countries are 
experiencing rapid changes and improvements in their living standards and 
conditions. Increasingly, modernization and industrialization are emerging from a 
process of transition and transformation. Yet, much of it remains poor and with out 
electricity. 
 
2.1.1 Geography and demography 
Mekong Countries cover a land area of some 2.3 million square kilometers. It shares 
area borders with China in the north, South China Sea in the south, Vietnam in the 
east and Myanmar (Burma) and Thailand in the west (Figure 2-1). 
 
 8 
 
 
Figure 2-1: Map of Mekong Countries 
 
The population of the Mekong region is 250 million, with 65.7 million of these people 
living within the hydrological basin of the Mekong River. Population growth is rapid 
and will likely continue in Laos, Cambodia, Myanmar and Vietnam (Figure 2-2). The 
regional population growth rate averages at approximately two percent, although 
there are marked variations, such as in some of the upland areas of Laos and 
Vietnam, where higher rates are not uncommon. The region also has an enormously 
wide range of different population densities. Laos, for example, has only 19 people per 
square kilometer, while Vietnam ranges from 300-500 people per square kilometer 
[Nilsson, et al, 2003]. 
 
The region’s population is overwhelmingly rural. It is estimated that 80 percent of the 
basin’s population lives in rural areas, basing their livelihoods on direct use of the 
region’s relative natural wealth. It is difficult to foresee urbanization trends in the future. 
 9
 
The World Resources Institute estimates that in 2020, 60-70% of the population will 
still live in rural areas Figure 2-3. However, the Nordic Institute of Asian Studies 
foresees a dramatic urbanization in the following years because of economic growth, 
as this process seems to have lagged in the region compared to other countries in Asia. 
 
0
50
100
150
200
250
300
350
400
2000 2025 2050
Year
M
illi
on
s
Yunnan
Vietnam
Thailand
Myanmar
Lao PDR
Cambodia
 
Source: [World Resources Institute, 1998; Asian Development Bank, 1999] 
 
Figure 2-2: Mekong Countries population projection  
 
 
0
10
20
30
40
50
60
1980 2000 2020
Year
%
 o
f t
ot
al
 p
op
ul
at
io
n Cambodia
Lao PDR
Myanmar
Thailand
Vietnam
Yunnan
 
Source: [World Resources Institute, 1998] 
 
Figure 2-3: Urban population projection 
 
The Mekong region is characterized by immense population diversity. The uplands 
are particularly complex in this regard. In Laos, there are as many as 68 ethnic 
groups comprising almost half of the population. But ethnicity is not a function of 
 10
nationality. Almost one million ethnic Khmers live in the Delta region of Vietnam, 
while there are more ethnic Lao in Thailand than there are within the borders of Laos. 
Livelihood systems have evolved over time in response to, for example: the 
hydrological regime, starkly contrasted geographic settings, extreme political events, 
and uneven access to resources. Although many communities are heavily dependent 
upon certain activities, in most cases, rural livelihood systems are a complex 
combination of several activities that contribute towards security. 
 
2.1.2 Climate condition 
Mekong Countries have very high levels of solar radiation, particularly in the southern 
region. The maximum average temperature during the hottest months, March to 
June, is 31 degrees Celsius, with a mean annual temperature of about 16 degree 
Celsius in the northern regions. Measured on a horizontal surface, daily solar 
radiation in the south (Cambodia and Vietnam) ranges from 6.5 kWh/m2 in April and 
May to 4.5 kWh/m2 in December, with an average of 5.5 kWh/m2. The central regions 
(Lao PDR and Thailand) have a similar pattern ranging from 4.5 – 6.3 kWh/m2 over 
the same months, with and average 5.0 kWh/m2. The northern region (Yunnan and 
Myanmar) range from 5.6 – 7.0 kWh/m2 over the same months, with average 6.0 
kWh/m2 [NCDC/World Climate/LaRC]. 
 
0
1
2
3
4
5
6
7
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
S
ol
ar
 ra
di
at
io
n 
 (k
W
h/
m
2 .d
ay
)
 
Figure 2-4: Solar radiation on horizontal surface of Thailand [DEDE, 1999] 
 11
0
1
2
3
4
5
6
7
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
S
ol
ar
 ra
di
at
io
n 
(k
W
h/
m
2 .d
ay
)
 
Figure 2-5: Solar radiation on horizontal surface of Cambodia [Li, 2002] 
 
0
1
2
3
4
5
6
Mountain of
the North
Plain of the
North
Central
region
Plateau of
the central
Delta
Mekong river
S
ol
ar
 ra
di
at
io
n 
(k
W
h/
m
2 .
da
y)
 
Figure 2-6: The average solar radiation in typical region of Vietnam [Le, 1997] 
 
Mekong Countries are characterized by regular rainfall patterns. The mean annual 
rainfall of the region is 1,500 mm but varies from 1,000 mm in the north (Yunnan) to 
3,500 mm in the centre and south region (Cambodia, Lao PDR and Vietnam). 
Rainfall varies significantly from year to year. 
 
2.1.3 Economic situation  
Economic growth in the region is rapid, although the countries vary a great deal in 
economic development. Southeast Asia, in general, enjoyed high economic growth 
rates in the early to mid 1990s (Figure 2-7). In 1997, the economic crisis struck, and 
growth rates became negative in many parts of Asia. In light of the crisis many 
 12
foresaw a slow recovery. However, in late 1999, it was evident that the region would 
recover more quickly than anticipated. Growth rates are expected to be 2-8% over 
the comingyears [Asian Development Bank, 1999/2001/2004]. 
 
-12
-10
-8
-6
-4
-2
0
2
4
6
8
10
12
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
Year
G
D
P
 (%
)
Cambodia Lao PDR Thailand Vietnam
  
Figure 2-7: Selected Mekong Country Gross Domestic Product during 1997-2005 
 
Still, poverty persists throughout the Mekong region’s urban and rural area, 
particularly many parts of the uplands face high levels of poverty. In the region, 
pervasive rural poverty is taken by many to be the single most critical failure of 
government policy. Therefore, the pursuit of economic growth is usually a prime 
objective of all governments. But there are questions related to the impacts of 
economic growth on equitable and sustainable use of environmental resources. 
 
The Mekong region has had large endowments of natural resources and has relied 
heavily on the export of natural resources in order to obtain income to import capital 
and goods. As a result, the Mekong region displays a high degree of dependence on 
the natural resource base.  
 
Table 2-1 shows the sector contribution to real Gross Domestic Product (GDP) in 
2000 in the six countries and compared to averages for low-, mid-, and high-income 
countries around the world. “Agriculture” includes agricultural and livestock 
production, logging, forestry, fishing, and hunting, and is therefore a good proxy for 
the whole range of land and water resources that we are concerned with. As can be 
 13
seen in the table, compared even to other poor countries, there is high resource 
dependence in Cambodia, Laos, and Myanmar. In the table, Thailand belongs to the 
Mid Income category. 
 
Table 2-1: Sector contribution to real GDP and growth rate per capita in 2000 (% and US$) 
 Agriculture Industry Service GNP/Capita
Regional:  
Cambodia 51 15 34 282
Laos 55 20 25 357
Myanmar 59 10 31 172
Thailand 11 40 49 2,543
Vietnam 26 31 43 330
Yunnan 19 49 32 479
World Average:  
Low income 28 28 43 350
Mid income 11 37 52 1,890
High income 6 31 63 25,890
Source: [Asian Development Bank, 2000/2001] 
 
Throughout the region, national governments, the private sector, and development 
agencies constitute a strong force pushing for increased economic integration. 
Regional economic and political integration is generally associated with improved 
conditions for growth, but it also has implications for the environment. 
 
In the Mekong region, economic integration occurs in parallel with an increased 
political cooperation, although a political integration, such as Europe (EU), is rather 
distant. The differences between the economic and political systems are still very far 
apart, with two highly centralized planning economies (Laos and Vietnam) and two 
highly market-oriented economies (Thailand and Cambodia). Therefore, integration in 
the region is characterised primarily by trade liberalization, market expansion through 
infrastructure investments, and relatively modest political cooperation. 
 
In the context of the Mekong region, the impact on trade flows and economic 
activities from the formal integration arrangements in the region cannot yet be 
estimated. Cambodia only joined ASEAN in 1999, Laos and Myanmar in 1997, and 
Vietnam in 1995. The Asian Development Bank – Greater Mekong Subregion (ADB-
GMS) programme was established in the early 1990s. The regional economic crisis 
abruptly changed trends of trade and growth. Therefore it is difficult to draw any 
conclusions. However, it is widely anticipated, and also a shared political vision, that 
 14
the region as a whole will experience an increased economic integration both 
regionally and globally. 
 
Expanding markets is an integral part of economic integration, and an explicit 
objective of many development agencies. It is supported primarily by infrastructure 
development and investment. Current and planned investments in infrastructure will 
continue to expand markets into remote areas in the uplands of Laos, Cambodia, and 
Vietnam, which will have wide-ranging consequences on resource use and access. 
 
2.2 Rural electrification situations   
 
2.2.1 Rural electricity needs and development 
For the poor, the priority is the satisfaction of such basic human needs as jobs, food, 
health services, education, housing, clean water and sanitation. Energy plays an 
important role in ensuring delivery of these services. 
 
Low energy consumption is not a cause of poverty and energy is not a basic human 
need. However, lack of energy has been shown to correlate closely with many 
poverty indicators. Addressing the problems of poverty means addressing its many 
dimensions. At the household level, although not recognised explicitly as being one 
of the basic needs, energy is clearly necessary for the provision of nutritious food, 
clean water and a warm place to live. 
 
In most rural households, particularly the poorest, the amount of useful energy 
consumed is less than what is required to provide a minimum standard of living. This 
has led to ‘norms’ being used by planning agencies when evaluating energy demand 
in rural areas. 
 
2.2.2 General characteristics of rural energy use 
Energy use in rural areas can be broken down into the household, agricultural and 
small-scale rural industry sub-sectors and services. Since the amount of energy use 
for services (health clinics, schools, street lighting, commerce, transport, etc.) is 
generally quite small in rural areas, it is often included in the rural industries sector. A 
few broad patterns in the use of energy in the rural areas of Mekong Countries can 
be described [WEC and FAO, 1999]. 
 15
 
• Households are the major consumers of energy, their share of gross rural energy 
consumption averages over 85%. Most of this is consumed in the form of traditional 
energy sources used for cooking and heating, which constitutes 80 to 90% of the 
energy used by households. 
 
• Agricultural activities consume from 2 to 8% of the total, depending on levels of 
mechanisation, mainly in the form of commercial energy used to power mechanical 
equipment and irrigation pump-sets. In general these statistics do not include human 
and animal power that provide the bulk of agricultural energy input for the basic 
agricultural activities.  
 
• Commercial energy, mainly kerosene and electricity where available, is mainly used 
for lighting, which on average constitutes about 2 to 10% of total rural consumption. 
Small amounts of electricity are used to operate radios, television sets and small 
appliances in electrified villages. This has serious implications for many rural 
electrification projects. Electricity demand curves in many rural areas are 
characterised by high peaks in the early evening hours and a low overall 
consumption, which means high investment in peak capacity installations and low 
returns. 
 
• The energy consumption of rural industries, including both cottage industries and 
village level enterprises, amounts to less than 10% of the rural aggregate in most 
countries. Woodfuel and agricultural residues constitute the principal sources of 
supply for these activities, with electricity sometimes providing some motive power. 
 
• Religious festivals, celebrations, burials and other occasional functions may also 
consume large amounts of fuel but may be missed by energy consumption surveys. 
 
 16
Dry cells, 
Kerosene, Candles
53%
Small system, Dry 
cells, Kerosene, 
Candles
12%
Kerosene candels, 
etc.
7%
Car battery, Dry 
cells, Candles, 
Kerosene
23%
Small system, Car 
battery, Dry cells, 
Candles
5%
 
Source: [Anil, 1996] 
 
Figure 2-8: Combinations of rural energy source in use in rural Laos 
 
Kerozene
16%
Generator
10%
Grid 
connected/Battery
5%
Grid 
connected/PV 
system
5%
PV/Battery
8%
PV system
3%
Battery
53%
 
Source: [Li, 2002] 
 
Figure 2-9: Rural energy in Pursat province, Cambodia 
 
2.2.3 Rural electrification 
In rural areas of Mekong Countries, the problem of electricity supplying rural 
communities is particularly alarming. Supplying power to these areas requires 
facilities that are not economically viable. However, government programs are under 
 17
way to provide this product that is vital to community well being. Table 2-2 shows the 
estimates of rural household access to electricity. 
 
Table 2-2: Estimates of rural household access to electricity 
Country Rural access
Cambodia 13%1 
Laos 9%
Myanmar 0.2%2 
Thailand 99%3
Vietnam 14%
Yunnan, China 89%4 
Source: [Davis, 1995/ 1Radka, 2005/ 2Samy, 2005/ 3 Kruangpradit, 2002/ 4 Zuming, 2001] 
 
A nation priority of Mekong Counties is to provide electrical power to people in rural 
areas, within normal budgetary constraints. Electricity must be introduced into rural 
areas in ways that maximize the technical, economic and social benefit. Another 
consideration is the source of electrical generation and the effects on the natural 
environment. 
 
However, the first attempts to synthesise the emerging experience with rural 
electrification in developing countries in the early 1980s revealed remarkably few, if 
any, positive impacts resulting from it. They concluded that benefits tended to be 
overestimated and the costs understated. More recent studies have often tended to 
support this initial conclusion. It has also been shown, however, that some rural 
electrification programmes have been an economic success, as measured by returns 
on investment. Some of the main distinguishing features between successful and 
unsuccessful cases have been identified: [WEC and FAO, 1999] 
 
• Cost-effectiveness. The goal of universal electric grid coverage often took 
precedence over considerations of cost or recognition of the point at which 
alternatives, such as diesel generators for local supplies or diesel engines for 
pumping, were more viable. 
 
• Enabling conditions and priorities for rural development. Rural electrification is more 
likely to succeed when the overall conditions are right for rural income growth, that is 
when incentives are present for the development of agriculture and agro-
industries and when electrification is based on, or accompanied by, complementary 
social and economic infrastructure development such as rural water supplies, health 
programmes, primary and secondary education and regional and feeder roads. 
 18
Surveys have shown consistently that these other factors often make rural 
electrification programmes more meaningful and successful by, for example, 
generating markets for electricity, leading to higher rates of return on investment. 
Rural electrification clearly contributes to, but is not a substitute for, other rural 
development interventions. As simple and straightforward as this may seem on 
hindsight, it has often been overlooked in the formulation of rural electrification 
programmes. 
 
Many earlier rural electrification interventions focused on extending the grid. Where 
grid power is possible and viable there should be no question about providing it. 
However, in the contentious debate between centralised and decentralised 
electrification, it has been asserted that decentralised systems do not compete with 
conventional grid extension. Photovoltaic systems can be used effectively for small 
isolated loads either as single dwelling systems for lighting, radio and television, or to 
power special services such as clinic refrigeration, small-scale water pumping or 
telecommunications. Clearly grid electricity is more versatile and once installed can 
usually allow for most conceivable increases in demand. However, decentralised 
options may be attractive for a number of other reasons. Where the demand is 
uncertain or latent, a diesel generator, for example, will require a lower initial 
investment and hence the risk of substantial financial loss is reduced. If demand 
does pick up, a grid connection could be made later and the diesel generator sold or 
used elsewhere. Small-scale hydro power, although site-dependent, may provide the 
least-cost option as well as providing a service comparable with grid supply. 
 
2.3 Rural electrification policy in selected Mekong Countries 
 
A priority in the Mekong is to provide electrical power to people in the rural areas as 
often as possible, within normal budgetary constraints. The services that become 
available through the use of electricity are essential for communities to maximize 
their economic and social development potential while ensuring that the natural 
environment is not compromised. Presently, the people living in rural areas of the 
Mekong Country still lack the option of public electricity grid service. Given the high 
cost of grid extension to utilities throughout the developing world, progress in 
expanding electricity service to non-electrified areas remains slower than population 
growth [Byrne, 1998]. Off-grid renewable energy systems represent an important 
 19
option for narrowing the electricity gap in rural areas of the Mekong Country. Each 
country in Mekong region sets up the planning of rural electrification. In this part, the 
policies about rural electrification from selected Mekong Countries are present. 
 
Cambodia: in July 1998 a corporate plan was formulated by taking into account the 
past performance and the future forecast of Electricité du Cambodge (EDC). The 
overall content of this plan consists of quality of supply with a reasonable price, 
customer preference, electrification improvement, human resource management, 
generation, and transmission and distribution improvement with quality and reliability 
of supply [SERT, 2000]. Table 2-3 summarize the overall strategic planning, targets 
and the goals of EDC.   
 
Table 2-3: Summary of the overall strategic planning, target and goals for EDC 
Strategy Target Goals 
Policy Quality of supply at a 
reasonable price 
Quality of supply: Voltage, Frequency 
Reliability:  
LOLP-20 time/yr 
Outage-18 h/yr (PHN), 20 h/yr (PRVE) 
Energy Price-$0.15 (PHN), $0.18 (PRVE) 
for regular customers. 
Customer 
Performance 
Customers willing to pay In-age duration: 60 minute (PHN) 
                          120 minute (PRVE) 
Connection Responsibility-72h 
Wholesalers = 0 
Electrification 
Improvement 
Improvement of the 
electrification within the 
coverage area  
Electrification rate: 108,000 (PHN), 8,500 
(SHV), 6,000 (KGC) 
 
Human Resources 
Management 
Updating of the capability 
and the efficiency of the 
personnel and improvement 
of their participation  
Customers per personnel – 90 
Upgrade the personnel skill – to 40% 
Salary US$ 60 
Financial Management Change EDC to an effective 
business entity 
Expense per Income – 0.94 
Current debt – 75 days 
Bad debt – 5% 
Plant availability  Construction of power 
stations and/or purchasing of 
the electricity at a reasonable 
price to serve the coverage 
area 
Goals: 103 MW and 505 GWh (PHN), 
            9.6 MW and 38 GWh (SKV), 
            4.3 MW and 18 GWh (SRP), 
            8.1 MW and 32 GWh (KGC), 
            5.7 MW and 23 GWh (BTB) 
Supply System Construction and upgrading 
the distribution system to 
reach good quality of supply 
and improvement of the 
system losses 
Availability of supply system: to ensure 
sufficient power supply for their coverage 
area. Improvement of the system losses: 
15% (PHN’s system) and 18% (PRVE) 
Note: PHN – Phnom Penh  SHV – Sihanoukvill  SRP – Siem Reap 
 KGC – Kampong Cham  BTB – Battambang  PRVE – Provinces  
 LOLP – Loss – Of – Load Probability   
 
In Myanmar, hydro and natural gas resources play large roles in generation of 
electric energy. These two resources will likely from the basis for generation 
 20
expansion, since these two resources are relatively available in Myanmar. The power 
development plan of Myanmar up to 2010 states hydro plants should be added in 
combination with combined cycle plants. After 2011, hydro power plants along the 
Thanlwin River will need to be developed. At that time, the surplus of Thanlwin 
hydropower could be transmitted to neighbor countries. 
 
In Vietnam, since the mid 90s, the strategy for electrification has been to electrify all 
province capitals and district towns and then gradually extend the network to 
communes. By the end of 1997 the national grid reached 100% of provincial capitals 
and 90% of district towns. In order to meet the target of 100% districts and 80% of 
communes electrified by the year 2000, Electricity of Vietnam (EVN) has decided to 
extend the national grid to all district towns and communes in the plain and coastal 
areas. From 2000 to 2010, the target will be to increase connection rates within the 
communes connected to the grid to achieve 50% of rural households in the 
mountainous areas. During this period old networks in the plain communes will be 
upgraded and rehabilitated. From year 2010 to year 2015, the target is to supply 
100% communes on the mainland and 90% of households [World Bank and 
Electricity of Vietnam, 1998].   
 
Thailand; at the end of June 2002, the Provincial Electricity Authority of Thailand 
(PEA) extended the existing electricity service area to cover 70,014 villages; this 
constitutes 99% of the total 70,715 villages under the care of the PEA. Of the 701 
villages without access to the electricity grid, 549 villages are located in forest 
conservation areas, wild animal conservation areas, forbidden areas or remote 
islands where the PEA is unable to extend the grid. The other remaining villages are 
located in high mountainous regions in the northern part of Thailand with scattered 
isolated families and hill tribes forming the bulk of the population in these areas. 
According to a study conducted on remote village electrification, it is not considered 
economical for the grid line to be extended to such areas. However, the Thai 
Constitution B.E. 2540 stipulates that one of the basic functions of the government is 
to provide essential public utilities, including electricity, to every Thai citizen. The 
electricity provided to the people must be of the same quality and cost, and produced 
from environmentally friendly power plant that does not cause negative social impact 
in the vicinity of the power plant. Thus, this provides a good opportunity for the 
Photovoltaic Systems, which can serve as a suitable environmentally friendly power 
 21
plant for these remote villages. Thailand is now the largest Photovoltaic user in 
Southeast Asia. In the year 2005, Thailand will have installed a total of approximately 
30 MW. The Photovoltaic project backed by the government accounts for much of 
this capacity. This project intends to improve the life of rural people by replacing old 
style candle light with modern fluorescent lamps. In addition to helping the residents 
in the rural areas, this project provides a good opportunity for the PV industry of 
Thailand to take off up. A total of 7,600 million baht (190 million US$) has been 
allocated from the government budget to carry out the Photovoltaic project. The 
project is managed by the Ministry of Interior and implemented by the PEA. Project 
completion is slated for April 2005 [Ketjoy, 2003/Khunchornyakong, 2004]. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 22
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 23
3 RENEWABLE HYBRID POWER SYSTEM 
 
The majority of the rural populations in the Mekong Country are dependent on 
biomass for meeting their energy needs. However, over-utilization of the natural 
energy resources is rendering the rural energy systems economically and 
environmentally unsustainable in many parts of the world. In order to deal with this 
crisis, the countries of the Mekong Country are beginning to strongly promote 
renewable energy technologies, based on solar, hydro and biomass resources. In the 
last two decades, several successes, as well as failures, have been experienced 
which could provide valuable information for formulating policies for better 
implementation of the renewable energy program in the future [Ketjoy, 2002]. 
 
3.1 Renewable energy potential in Mekong Country 
 
As fossil fuel energy becomes scarcer, Mekong Country will face energy shortages, 
significantly increasing energy prices and energy insecurity within the next few 
decades. In addition, Mekong Country’s continued reliance on fossil fuel consumption 
will contribute to accelerating the rates of domestic environmental degradation and 
global warming. For these reasons, the development and use of renewable energy 
sources and technologies are increasingly becoming vital for sustainable economic 
development of Mekong Country. Hydropower, biomass, wind power and solar 
energy will be the major resources that provide Mekong Country with most of its 
renewable energy in the future. In this study, the potentials and limitations of these 
renewable energy sources were assessed for supplying the future needs of Mekong 
Country. The potential of renewable energy source of the region except Yunnan, 
China are present below.   
 
3.1.1 Hydro energy 
Cambodia is the one of the regions richest countries in hydropower resources, 
having the third largest hydropower potential in the Mekong Basin. According to the 
latest preliminary study the total hydropower potential of the country is estimated at 
10,000 MW, of which 50% is in the Mekong, 40% in its tributaries and the remaining 
10% in the south-western coastal area outside the Mekong river basin. Cambodia will 
need to use its hydropower potential in order to meet future electricity demand, to 
reduce the dependence upon imported fuel, and to allow the exchange of 
 24
hydropower with neighboring countries. Before the civil war, the Kirirom hydropower 
station was running with an installed capacity of 10 MW, and energy was delivered to 
Phnom Penh through a 110 kV transmission line over a distance of 120 km. This 
plant was completed in 1968 as the first hydropower station in Cambodia, but it was 
completely destroyed during the war after only 13 months of operation. However it is 
being restored by Austrian and Swedish Aid projects. The Prek Thnot project with an 
installed capacity of 18 MW was implemented near the Kirirom I hydropower station, 
but the construction was interrupted in 1970 due to the war. Since 1992 there has 
been only one small hydropower station in Cambodia, and all of the operating 
generators now are diesel and oil-fired depending on imported oil.  
 
Lao PDR has a hydropower potential of about 22,500 MW within its territory. Up to 
now, less than 2% of the total potential has been developed with 55 to 60% of the 
production exported to neighbouring countries. Considering the topography of the 
country, it can be expected that macro hydropower could be an important source of 
electrical and possibly mechanical power to rural mountainous areas. At present, 
macro hydropower stations with a total installed capacity of 615 MW have been 
completed. Lao has 60,000 cubic maters of renewable water resources per capita, 
more than any country other country in Asia. There are 35 small/micro hydropower 
stations that range from 5 kW to 1,600 kW that have operated in parts of country with 
total installed capacity of 5,653 kW. In remote villages in the North of Laos, 
hydropower is already being used for lighting, rice mills etc. In recent years, many 
families in mountainous areas and villages close to streams have been using small 
pico hydropower generators of capacity between 200 – 5,000 W for their electricity 
demands. These generators, imported from China and Vietnam, are not high quality 
but the price is very attractive to Lao PDR [Douangvilay, 2002]. 
 
Myanmar planed to establish a mini-hydro system in 1980. Until 1988, 12 units were 
commissioned and another 9 units were completed by 1991. Nine more mini-hydro 
projects are currently under way. The rapid progress since 1989 is the result of the 
change in policy towards involving the people in the projects through financial and 
voluntary service contributions [SERT, 2000]. 
 
 25
In Thailand small hydro power plants with installed capacity of 200 – 6,000 kW have 
been established since 1980. At present, 23 projects with a total installed capacity of 
72.4 MW have been completed. Another two projects with a total installed capacity of 
9.95 MW are under construction. Village level or micro hydro power plants with 
installed capacity smaller than 200 kW have also been constructed. A total installed 2 
MW from 71 projects has been completed. Another two projects with a total installed 
capacity of 210 kW are under construction [SERT, 2000].  
 
Vietnam receives high annual rainfall and has a large network of rivers, streams and 
springs. The estimated total potential hydro resource is about 20,000 MW at the 570 
identified sites; the total installed hydropower capacity was only 2,824 MW in 1995. 
Currently hydropower is used to produce around 75% of the country’s electricity. 
People living in rural villages have turned to family hydro units to get electricity for 
lighting and for charging batteries, which are subsequently used for lighting, radio 
and television [SERT, 2000].  
 
3.1.2 Biomass energy 
In almost all Mekong Countries, biomass energy plays a major role in satisfying the 
rural energy demands. The potential of biomass in each country is presented below. 
 
Cambodia, according to an estimate by the FAO, wood fuel consumption in 1994 was 
1.6 MTOE, and accounted for 84% of the total energy consumption in the country. 
The total potential available from wood fuels during the same year was 24.5 MTOE. 
Besides, an estimate amount of 0.17 MTOE of agro-industrial processing residues 
were also available as fuel in 1994. Due to the lack of modern technology in this field 
the development of the biomass energy is still very low. In Cambodia biomass 
resources are basically from agriculture wastes and are generally used for cooking 
and small handicrafts are rural areas. Biomass is also used in the industrial sector for 
copra drying and stream generation. However, no reliable estimates of the amount of 
biomass energy consumption for these purposes are available [SERT, 2000]. 
 
 In Lao PDR, biomass energy plays a major role in satisfying the rural energy 
demands of Lao PDR. The Science Technology and Environment Agency (STEA) 
estimates that wood fuels account for the major part, amounting to about 74.4% of 
 26
total energy consumption in 1993. According to an estimate of FAO wood fuel 
consumption in 1993 -1994 was 2.329 million tons and accounted for 89% of total 
energy consumption in Lao PDR. Also, total potentially available wood fuel during the 
same year was 49.086 million tons. It is estimated that about 92% of the households 
use wood fuels for cooking. Beside from wood fuels, an estimated amount of 0.343 
million tons of agro-industrial processing residues were also available for use as fuel 
in 1993 -1994. The energy potential of biogas from recoverable animal wastes in Lao 
PDR has been estimate to be about 189 KTOE/year. Since 1996, the STEA with the 
objective of rural area development and promotion of renewable energy utilization 
has a stated objective of biogas utilization. This is also aimed at increasing the use of 
organic manure in agriculture and curtails the excessive use of chemical fertilizers. At 
present, several biogas plants with capacities ranging from 12 to 16 m3 have been 
utilized. This will also help decrease the consumption of fuel wood from forests 
[Douangvilay, 2002]. 
 
In Myanmar, Wood fuel made up 75% of total primary energy consumption in the 
country. This is equivalent to 8,751 KTOE, of which 380 KTOE or 4.35%, was used 
to produce 111 KTOE used by both the rural and urban populations, while charcoal 
was used mainly by the urban population. Agriculture residue represents a 
substantial fuel source. Sufficient data is not available to make an estimate of its 
potential except in the case of paddy husk. Available data for the year 1988 – 1989 
place paddy husk production at 823.8 KTOE, and the production of other crop 
residue at 1,065.9 KTOE. The amount available for use as energy is estimate to be 
271.88 KTOE of paddy husk and 353.25 KTOE of other crop residue. Paddy straw is 
usually put to higher economic value uses, such as cattle fodder. The supply for the 
year 2000 -2001 is 1,455.3 KTOE of paddy husk and 1,567.35 KTOE of other crop 
residue. The energy available for utilization is projected to be 1,091.5 KTOE of paddy 
husk an 1,175.5 KTOE of other crop residue [SERT, 2000].    
 
Thailand has a fairly large availability of biomass energy resources. It can be utilized 
in two forms: traditional and modern. In Thailand, the traditional form of biomass 
energy utilization is mostly applied by domestic sectors and small scale commercial 
sectors by direct combustion with rather lower efficiency. In the modern form of 
biomass energy utilization, biomass energies are utilized by newly developed 
 27
biomass energy conversion technologies in the form of liquid, gas and electricity such 
as by producing ethanol, methanol, bio-diesel, biogas and cogeneration. In 2001, the 
final energy consumption supplied from biomass was about 8.4 MTOE, of which 3.3 
MTOE was from wood fuel, 2.3 MTOE from charcoal, 0.9 MTOE from paddy husk 
and 1.99 MTOE from bagasse. The share of biomass was about one-fifth (18%) of 
the final energy consumption in the country. It was mainly used in residential and 
commercial sectors. Almost all fuel wood and charcoal are used for household, while 
almost all paddy husk and bagasses are used by manufacturing industries. There are 
a large amount of unexploited biomass resources such as animal wastes, industrial 
wastes, municipal solid wastes and the other agriculture residues [Sathienyanon, 
2003].  
 
In Vietnam, the main biomasses are wood fuel, charcoal, agriculture residues and 
animal waste. According to an estimate of FAO, the amount of wood fuel 
consumption in 1994 was 8.8 MTOE. Besides wood fuels, a considerable amount of 
agro-industry processing residues are also available as fuel in Vietnam. About 32% 
of all the agro-industry processing residues in Vietnam are used for energy while the 
rest is wasted. The residues generated from logging activities and wood processing 
industries, as well as the amount that may be available for energy use, have been 
estimated to be 2.97 MTOE. Similar estimates by FAO put the figure for the year 
1994 at 6.35 MTOE of ago-industrial processing residues representing 2.37 MTOE of 
energy resource. The combustion of wood fuel and other biomass fuels such as rick 
husk, bagasse and wood residue has traditionally been in rural industrial furnaces 
and small-scale industries such as brick kilns and sugar mills. In the domestic sector, 
the energy-using devices are primarily cook stoves, which have average efficiency in 
the range of 10-15%. The Institute of Energy has been involved in the development 
of improved cook stoves with the co-ordination of FAO’s Regional Wood Energy 
Development Programme (RWEDP), the World Bank and the Energy Institute of 
Francophonic Countries (IEPF) [SERT, 2000]. 
 
3.1.3 Wind power 
Up to the present, the generation of electricity from wind has yet to be implemented. 
Cambodia has potential in this resource, especially at the coast and in the 
mountainous regions where the wind velocity is generally about 10 m/s. 
 28
Measurements during 1981 – 1990 at Phonom Pehn indicate that the average wind 
velocity varies between 4.8 and 14.8 m/s in January and July respectively. There are 
five units installed using wind energy for water pumping implemented by an NGO for 
irrigation Prey Veng Province [SERT, 2000]. 
 
The potential of wind energy in Lao PDR has not yet been assessed [Douangvilay, 
2002]. In 1997, a demonstration wind power plant was installed with a capacity of 1 
kW at Xiengkhuang province. Unfortunately, this plant can operate only during the 
period of dry season from December to March [SERT, 2000].  
 
In Myanmar, Central Research Organisation (CRO) carried out wind velocity surveys 
in a number of localities in the central regions of the country in the early 1980s. The 
results obtained can be found in the reference document. Based on that, a number of 
experiments have been carried out to assess the feasibility of wind turbine based 
water pumping and electricity generation. In certain remote hilly and coastal areas, 
the wind velocity is much higher than average for the country [SERT, 2000].   
 
The wind map of Thailand indicates that there are good wind areas during the North-
East monsoon, starting from November until late of March. The areas in the Class 3 
category (6.4 m/s wind speed at 50m height) or higher are located along the eastern 
coastline of the southern part of the Gulf of Thailand from Nakhon Srithammarat 
through Songkla and Pattani provinces, and also over the ridge of Doi Intanon in the 
Chiangmai province. In addition, the assessment indicates that there are good wind 
areas during the South-West monsoon, from May until mid-October; they are located 
on the west side of Thailand stretching from the northern end of the southern region 
into the parts of the northern region. These areas occur in the mountain ranges 
through Phetchaburi, Kanchanaburi and Tak provinces. Good wind areas during both 
the North-East and the South-West monsoons are located in the mountains of the 
national parks in the southern region. These areas are in Krang Krung national park 
in Suratthani province, Khoa Luang and Tai Romyen national park in Nakon 
Srithammarat, Sri-Phangnga national park of Phangnga, and Khoa Phanom Bencha 
in Krabi province. The fair wind areas in the Class 1.3 to Class 2 category (4.4 m/s 
wind speed at 50 m height) or higher are located on the west side of the Gulf of 
Thailand in Phetchaburi, Prachuabkirikan, Chumphon and Suratthani provinces. 
 29
These fair wind areas also occur over mountain ridges in the northern region of the 
country at Chiangmai and in the north-eastern region in Phetchabun and Loei 
provinces, which are influenced by the North-East monsoon. They also occur under 
the influence of the south-west monsoon in the western coastal areas of the southern 
region at Phangnga, Phuket, Krabi, Trang and Satun, and also on the eastern side of 
the Gulf of Thailand in Rayong and Chonburi provinces [DEDP, 2001]. 
 
Vietnam has a long coast of 3,000 Km and thousands  of Islands. In the coastal 
regions, the wind average speed is 5.6 m/s and over 8.0 m/s on Islands [CORE, 
2003]. Wind power has been put into application with some types of wind turbines for 
water pumping and electricity generation, but the potential for larger scale utilization 
for grid quality power generation still needs to be study [SERT, 2000].  
 
3.1.4 Solar energy 
Cambodia has a tropical climate with favourable conditions for the utilization of solar 
energy. Measurements made during 1981-1988 at Phnom Penh indicate that the 
average sunshine duration varied between 6.1 and 9.7 hours per day in August and 
December respectively [SERT, 2000]. The country has big potential; solar radiation in 
kWh/m2.d is high: 4.24 in August to 6.34 in March, with the year average of around 
5.4 [CORE, 2003]. 
 
Lao PDR is situated in the tropical zone in Southeast Asia. The annual mean daily 
global solar radiation in the country is in the range 4.50-4.70 kWh/m2.d, which makes 
it a potentially good location for solar energy utilization. Solar photovoltaic technology 
has been introduced in Lao PDR since the 1980s and subjects have been applied 
successfully in many localities, bringing benefits in remote areas that cannot be 
reached by national grids [Douangvilay, 2002]. 
 
Myanmar has limited reliable solar energy data. Solar energy has been put into 
application with some types of solar cooker, drier, water still and battery charging but 
the potential for larger scale utilization for quality power generation still needs to be 
studied. Only some data of average sunshine hours has been found in the reference 
[SERT, 2000].  
 
 30
In Thailand, the radiation data has been found from the solar radiation maps of 
Thailand made by DEDP. Most parts of the country receive the highest solar 
radiation during April and May, with the values ranging from 5.56 – 6.67 kWh/m2.d. 
The yearly average daily global solar radiation map demonstrates that the region that 
receive highest solar radiation are in the northeast and the central parts of the 
country. These regions, which receive the yearly average daily radiation of 5.23 – 
5.56 kWh/m2.d, represent 14.3% of the country. It was found that 50.2% of the area 
of the country receives the yearly average daily global solar radiation in the range of 
5.00 – 5.23 kWh/m2.d and only 0.5 % receive radiation less than 4.44 kWh/m2.d. The 
yearly average daily global solar radiation for the whole country is 5.06 kWh/m2.d. This 
value indicates that Thailand has a fairly high solar energy potentials [DEDP, 2000]. 
 
The best climatic conditions for the utilization of solar energy in Vietnam are found in 
the Southern region. Annual solar radiation in Vietnam is in the range of 3.69 to 5.9 
kWh/m2, with a yearly average sunshine duration of 1,600-2,720 hours. The solar 
radiation of Vietnam is an important natural resource. It has quite good potential. The 
average total solar radiation is about 5.00 kwh/m2.d in almost Middle and Southern 
provinces of Vietnam. In the Northern provinces, the solar radiation is lower, about 
4.00 KWh/m2.d approximately. South of the 17 in parallel, the radiation is good and 
maintains continuously all year. It reduces about 20 % from dry season to rainy 
season [CORE, 2003].  
 
3.2 PV hybrid system technology category 
 
To date, PV systems for electrification such as central PV power plants for rural area 
and roof-top grid-connected PV system for urban households are not economically 
viable. Based on current economic conditions Solar Home Systems are comparable 
in cost with grid extension. But the potential for these systems is significant-about 10 
MWp for Solar Home Systems and 64-640 MWp for roof-top grid connected PV 
systems [AIT, 1998]. 
 
However, a PV system can be suitable for certain applications and niches, such as 
remote areas where conventional energy is very expensive or if conventional 
electrification is not always suitable. One of the most promising applications of 
renewable energy technology is the installation of hybrid renewable energy systems 
 31
in rural areas, where the cost of grid extension is prohibitive and price of fuel 
increases. Renewable energy sources, such as solar energy, wind or hydropower, 
provide realistic alternatives to engine driven generators for electricity generation in 
rural areas. The widely used term Hybrid Energy System describes a stand-alone 
energy system, which combines renewable and conventional energy sources with 
batteries for energy storage. 
 
Category of PV-diesel generator hybrid system 
PV-diesel generator hybrid systems generate electricity by combining a photovoltaic 
array with a diesel generator. They can be categorized according to their 
configuration as [Wichert, 1999 / Markvart, 2000 / Ketjoy, 2002]: 
 
• Series hybrid system 
In the series hybrid system (Figure 3-1), the energy from diesel generator and a PV 
array are used to charge a battery bank. The diesel generator is connected in series 
to the inverter to supply the load. The diesel generator cannot supply the load 
directly. The inverter converts DC voltage from the battery to AC voltage and 
supplies to the load. The capacity of the battery bank and inverter should be able to 
meet the peak load demand. The capacity of diesel generator should also be able 
meet the peak load and charge the battery simultaneously. 
 
Gen
PV Array
Controller
DC BUS
Battery Bank
Diesel Generator
AC Load
~
~
Inverter
Rectifier/
Battery Charger
 
Figure 3-1: Series PV-diesel generator hybrid system 
 
• Switched hybrid system 
The switched hybrid system (Figure 3-2), the battery bank can be charged by the 
diesel generator and the PV array. The load can be supplied directly by the diesel 
 32
generator. If the diesel generator output power exceeds the load demand, the excess 
energy will be used to recharge the battery bank. During period of low electricity 
demand, the diesel generator is switched off and the load is supplied by the PV 
array, together with stored energy from the battery bank. When comparing the overall 
conversion efficiency, switched systems is more efficient than the series system. 
 
PV Array
Controller
DC BUS AC BUS
 InverterBattery Bank
Diesel Generator
AC Load
~
~
Battery Charger
1
2 change-over
switch
Gen
 
Figure 3-2: Switched PV-diesel generator hybrid system 
 
• Parallel hybrid system 
 A parallel hybrid system is show in Figure 3-3. The diesel generator can 
supply the load directly. The PV array and the battery bank are connected in series 
with the bi-direction inverter to supply the load. During low electricity demand, excess 
energy from PV array is used to recharge the battery bank. The bi-directional inverter 
can charge the battery bank when excess energy is available from the diesel 
generator. Parallel hybrid energy systems have two major advantages over the 
series and switched hybrid system. The inverter plus the diesel generator capacity, 
rather than individual component ratings, limit the maximum load that can be 
supplied. Typically, this will lead to a doubling of capacity. Second, the capability to 
synchronize the inverter with the diesel generator allows greater flexibility to optimize 
the operation of the system.  
 
 33
~
PV Array
Controller
DC BUS AC BUS
Bi-direction
Inverter
Battery Bank
Diesel Generator
AC Load
Gen
  
Figure 3-3: Parallel PV-diesel generator hybrid system 
 
3.3 Prototype of hybrid system for Mekong Country  
 
3.3.1 Modular Systems Technology (MST) 
Renewable energy can be efficiently integrated in off-grid regions. In order to offer an 
uninterruptible power supply, hybrid systems equipped with batteries or combustion 
engines are applied. The Modular Systems Technology, which supports the design of 
modular construction kits in different power ranges, has been developed [Landau, 
2002].  
 
The prototype of a hybrid system for Mekong Country is different from the general 
type as presented above. This system concept was innovated by the ISET. The 
system is called the AC-coupled modular expandable hybrid system. This system is 
characterized by a stipulated energy coupling (AC-bus bar with e.g. 230/400 V, 50 
Hz), a standardized information exchange and a supervisory control. This approach 
allows setting up an adaptable and expandable system structure, thus covering 
almost every supply situation; but it means that the generators integrated into the 
system have to be equipped with special control features [Strauss et. al, 2003].  
 
Figure 3-4 shows a general diagram of stand-alone off-grid supplied mainly with 
renewable energy source. The generators can supply the load directly. PV 
generators and battery storage connected in series with grid inverter and bi-direction 
inverter respectively supply the load. A battery storage and bi-directional inverter can 
be applied to balance renewable energy sources to match the load demand. The 
 34
advantage of this system is that it can easily increase output power and is extendable 
from a single phase to three phases. 
 
PV Generator Diesel Generator
System loadsAC-Bus 230 V/1~
~~ ~
BatteryBattery
G
MLamp
Electrical
Machine  
 
PV module & string inverters Diesel Generator
System loadsAC-Bus 400 V/3~
Battery Bank
G
M
Electrical
Machine
~ ~ ~
~ ~ ~
Lamp
Lamp
Lamp
 
Figure 3-4: Single and three phase AC-couple modular expandable hybrid system   
 
According to the actual demand, PV generators can be connected to the AC bus in 
the same way as it standard grid-connected systems. In other words the string 
concept for inverters, which has been successfully introduced to grid-connected PV 
systems, can be used in stand-alone plants as well. Special care has to be taken 
when using several bi-directional inverters (battery inverter) in parallel. In this case 
the parallel bi-directional inverters have to divide the loads equally in both directions 
in case of equal nominal power or proportionally to this figure in case of different 
values. Conventionally this requirement can be performed using a master slave 
concept. With a novel approach it could be demonstrated that parallel operating of bi-
directional inverters can be performed without using any communication between 
those units [Schmid, 2001]. 
 
 
 35
3.3.2 Classes of power units 
The components of such modular systems can be distinguished by their function as 
either a grid forming unit, a grid supporting unit (controllable generators) or a grid 
parallel unit (uncontrollable generators and loads) [Strauss et. al, 2003].  
 
Grid forming unit: The grid forming unit controls grid voltage and frequency by 
balancing the power of generators and loads. Standards systems contain just one 
grid forming unit as a master which can be a diesel generator set or a battery 
inverter.  
 
Grid supporting unit: Being similar to traditional electrical supply system, the grid 
supporting unit’s active and reactive power is determined by voltage and frequency 
characteristics which allow primary control and power distribution. 
 
Grid parallel unit: These units comprise loads and uncontrollable generators. 
Uncontrollable generators are e.g. wind energy converters without control or PV 
inverters for grid connection. Both devices are designed to feed as much power into 
the grid (island grid) as possible.  
 
3.3.3 The prototype system at SERT 
The hybrid system prototype for rural area of the Mekong Country is installed at the 
Energy Park area of SERT (Figure 3-5) under the framework of the EU project: 
Mini-grid-Kit NNE5-1999-00487 and the framework work of the Energy Park 
Project and NRCT project: A Study of Mini – Grid Concept for the Villages 
without Electricity in Thailand (MGCT). The system consists of 2.0 kWp PV 
generator, 5.0 kW diesel generators, 18.0 kWh battery bank (deep cycle lead-acid 
type), 2.0 kW Grid connected inverter, 3.3 kW Battery inverter (Bi-directional inverter), 
Sunny Boy Control and Delphin data logger for measuring, monitoring and recording 
electrical parameters and 3.0 kW variable simulator load [Ketjoy, 2003]. Appendix 
A presents the detailed drawing of the System. 
 
 36
SB
AC-Bus 1 ~ 230 V 50 Hz
~
kWh
Load no. 1
PV
SI
BB
~
DG
SBC
System loads
kWh
Load no.  2
G
 
 
 
 
 
 
   
 
Figure 3-5: PV Hybrid System prototype at SERT 
 
3.4 Testing and monitoring of the prototype  
 
The AC-couple modular expandable hybrid system concept is very new for the 
Mekong Countries, there is no experience used from the real site. With the budget 
constraint, the prototype could not install in the real rural areas. To simulate the 
system under the same conditions of the rural villages, the simulator load has to 
install for this research. This simulator design very simply by using 6 x 500 W 
heaters, variable loads control system as possible to operate load from 10 – 3,000 W 
and the analog timer system for loads profile setting (Appendix A).  
 
3.4.1 Test method 
Figure 3-6 presents the PVHS performance testing procedure. First the different load 
profile data from CORE data base are used for this testing. Second, input the load 
PV: PV generator “BP275F”, 75W x 26 modules    BB: Battery bank “Exide OPzS 305”, 60V, 305 Ah 
DG: Diesel generator “Honma 5GFLE”, 5 kW         SB: Grid connected inverter “SMA Sunny Boy 1700E”, 2.0 kW
SI: Battery inverter “SMA Sunny Island”, 3.3 kW     SBC: Sunny Boy Control data logger   
 37
profile (example of load profile show in Figure 3-7 to 3-11) to the load simulator by 
setting up an analog timer. Third, test the PVHS with loads input and record the data. 
Repeat the process by changing the selected load profile. 
  
 
Figure 3-6: PVHS performance testing procedure with different loads profile pattern  
 
 
0
0.5
1
1.5
2
2.5
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Village1
Village2
Day time (h)
Lo
ad
 d
em
an
d 
(k
W
)
 
 
Figure 3-7: Load profile of small villages in northern of Thailand [Ketjoy, 2003] 
Variable load 10 – 3,000 W
Analog timer
Load Simulator
• 6 step variable load simulator for 
PVHS testing 10 – 3,000 W
• Running by timer control
Different loads profile 
pattern from rural villages 
• Different loads profile from 
rural villages of Lao, China, 
Cambodia, Thailand
0
500
1000
1500
2000
2500
3000
3500
1:
00
 - 
2:
00
2:
00
 - 
3:
00
3:
00
 - 
4:
00
4:
00
 - 
5:
00
5:
00
 - 
6:
00
6:
00
 - 
7:
00
7:
00
 - 
8:
00
8:
00
 - 
9:
00
9:
00
 - 
10
:0
0
10
:0
0 
- 1
1:
00
11
:0
0 
- 1
2:
00
12
:0
0 
- 1
3:
00
13
:0
0 
- 1
4:
00
14
:0
0 
- 1
5:
00
15
:0
0 
- 1
6:
00
16
:0
0 
- 1
7:
00
17
:0
0 
- 1
8:
00
18
:0
0 
- 1
9:
00
19
:0
0 
- 2
0:
00
20
:0
0 
- 2
1:
00
21
:0
0 
- 2
2:
00
22
:0
0 
- 2
3:
00
23
:0
0 
- 2
4:
00
24
:0
0 
- 1
:0
0
Time
En
er
gy
 c
om
su
m
pt
io
n 
(W
)
0
200
400
600
800
1000
1200
1400
1600
1:
00
 - 
2:
00
2:
00
 - 
3:
00
3:
00
 - 
4:
00
4:
00
 - 
5:
00
5:
00
 - 
6:
00
6:
00
 - 
7:
00
7:
00
 - 
8:
00
8:
00
 - 
9:
00
9:
00
 - 
10
:0
0
10
:0
0 
- 1
1:
00
11
:0
0 
- 1
2:
00
12
:0
0 
- 1
3:
00
13
:0
0 
- 1
4:
00
14
:0
0 
- 1
5:
00
15
:0
0 
- 1
6:
00
16
:0
0 
- 1
7:
00
17
:0
0 
- 1
8:
00
18
:0
0 
- 1
9:
00
19
:0
0 
- 2
0:
00
20
:0
0 
- 2
1:
00
21
:0
0 
- 2
2:
00
22
:0
0 
- 2
3:
00
23
:0
0 
- 2
4:
00
24
:0
0 
- 1
:0
0
Time
En
er
gy
 C
om
su
m
pt
io
n 
(W
)
0
500
1000
1500
2000
2500
3000
3500
4000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Daytime (h)
Lo
ad
 (W
h)
Summer
Winter
0.00
500.00
1000.00
1500.00
2000.00
2500.00
3000.00
1 3 5 7 9 11 13 15 17 19 21 23
Daytime (h)
Lo
ad
 (W
h)
12/7/1999 Tuesday
4/15/2000 Monday
7/1/2000 Saturday
Input load profile
to simulator
Different
load
profile
Start
Test PVHS with
load input
Return
Record data
parameter
 38
 
 
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time
En
er
gy
 c
om
su
m
pt
io
n 
(W
)
0
100
200
300
400
500
600
700
800
900
1000
Irr
ad
ia
nc
e 
(W
/m
2 )
 
 
Figure 3-8: Load profile of a single village in Chiangria, Thailand [SERT] 
 
 
 
0
200
400
600
800
1000
1200
1400
1600
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Time
En
er
gy
 C
om
su
m
pt
io
n 
(W
)
 
 
Figure 3-9: Load profile of a Ban Pang Praratchatan village, Thailand [SERT] 
 
 39
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Single household
Lo
ad
 de
ma
nd
 (k
W
)
Daytime (h)
 
 
Figure 3-10: Load profile of a single household in Thailand [Ketjoy, 2003] 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 3-11: Hourly of load in Luo Buo Tai Zi, Xinjiang, China [Nieuwenhout, 2001] 
 
 
3.4.2 Data monitoring system 
The electrical system parameters of the hybrid system are monitored using the 
Sunny Boy Control (SBC) data logger from SMA Company and Delphin data logger. 
The SBC receives system data from the Sunny Boy (SB) and from the Sunny Island 
(SI) via an RS485 Interface. These data can be read by a PC using an RS232 
 40
interface. Further evaluation and data processing can be done with the Sunny Data 
Control software, and after exporting the data in a common file format, it can be read 
with any other software [SMA, 2000]. 
 
Parameter Device Unit
Solar radiation Delphin W/m2
Ambient temperature (Tamb) Delphin °C
Module temperature (Tmodule) Delphin °C
Load consume  Delphin kWh
PV voltage SBC V
PV current SBC A
Grid voltage SBC V
Grid current SBC A
Grid frequency SBC Hz
SB energy yield  SBC kWh
SB power SBC W
Batt voltage SBC V
Batt current SBC A
Batt power in/out SBC W
Batt temperature SBC °C
SOC batt SBC %
 
Figure 3-12: Data monitoring system  
AC Bus 230 V 50/60 Hz
SI
DC voltage
DC current
V
A
SB ~
energy yield
Tmodule
Solar radiation
DG
G
Tbat
Battery voltage
Battery current
BB
Tamb
Diesel generator energy meter
Consumer energy meter 3
Consumer energy meter 2
Consumer energy meter 1
Water pumping
kWh
House no. 1 House no. 2
kWh
House no. 3
Pumping system energy meter
kWh
kWh
~
kWh
kWh
Grid frequency
Energy input/output
of battery
Grid voltage
Gird current
R
S 
23
2
kWh
V
A
f
SBC
kWh
Delphin
 41
3.4.3 Data analysis  
The energy flow through the system and the performance parameters were 
calculated on the basis that Gt is the solar energy incident on the PV modules, while 
Enominal is the maximum (theoretical) energy that could be delivered by the modules 
and Epv use is the actual energy (load consume or AC energy used) used in a day. 
The nominal energy delivered by the PV module Enominal is obtained by [Ketjoy, 
2002/Ketjoy, 2004]:  
 
                     Enominal = ∫
period
STCmodulemodulet dtηAG    [kWh]          (3.1) 
 
Where 
                    ηSTC,module = 
STCmodule
modulerate
GA
P
              (3.2) 
 
and ηSTC,module is the PV module efficiency under standard testing conditions (1,000 
W/m2, 25 °C and Air mass 1.5), Prate module is the power rate of module from the 
manufacturer under STC taken as 75 W, GSTC is the solar radiation incident on the 
PV modules taken as 1,000 W/m2, Amodule is the area of the PV module. 
 
The actual energy used by the loads during the day when the measurements were 
done can be calculated from 
 
                     Epv use = Econsume   [kWh]                         (3.3) 
 
Where, Econsume is the energy consumption measured by kWh meter. Figure 3-12 
shows a schematic of the components of the PVHS, and the location where the 
measurements were taken.      
 
The Solar Fraction Fsol is the ratio, as a percentage, of the used solar energy Epv use, 
to the total energy demand Edemand. 
 
                       
demand
use pv
Sol E
E
F =  (3.4) 
 42
The Performance Ratio (PR) is a characteristic value for the losses. It indicates how 
close a system in operation comes to the maximum performance given by the solar 
generator. The performance ratio is defined as the ratio of used solar energy to the 
nominal energy. The nominal energy represents a theoretical energy production of 
the PV generator, operated permanently at STC conditions and without any further 
energy losses. The performance ratio is defined as: 
 
                      PR = 
nominal
use pv
E
E
                         (3.5) 
 
This equation gives the ratio of used solar energy to the nominal producible energy, 
i.e., the production of energy Enominal that would be theoretically possible if the PV 
generator always works with the efficiency (ηSTC) reached under standard testing 
conditions. 
 
The Final Yield (FY) gives the daily mean value of the used solar energy per kilowatt 
installed power of the solar generator (Pnominal = k Prate module) installed. 
 
 
norminal
use pv
day.P
E
FY =      [h/d] (3.6) 
  
The mean PV generator efficiency ηPV depends on the radiation conditions ESolar as 
well as on the particular operating conditions of the PV generator. It can also be 
estimated from equation (3.7) as: 
   
                      
Solar
PV
PV E
E=η                            (3.7) 
 
The quantity ηPV is influenced by the variation of efficiency due to physical effects 
(dependence of radiation and module temperature, impact of the solar radiation 
spectrum, reflection on the module’s surface) as well as by the losses of the system 
that are caused by the operating conditions (effect of mounting method, deviations of 
the operating point from the maximum power point, inverter losses, battery losses 
and etc.). 
 43
3.4.4 Technical performance evaluation results  
The technical parameters of PVHS were evaluated by radiation, temperature and 
electrical measurements. The system performance at SERT installations was studied 
by measuring (at 15 minute intervals during a day of year: Apr 03 – Mar 04) solar 
radiation, ambient and cell/module temperature, and energy consumed by the load. 
The evaluations of the system performance are presented as [Ketjoy. 2004]: 
 
Energy consumption 
The yearly energy consumption of this system is 2,619 kWh, average daily energy 
consumption is 7.2 kWh/d and the energy produced by the diesel generator over the 
year is 227 kWh. Figure 3-13 present the correlation of daily average energy 
consumption and diesel generator energy production for each month during the year.  
  
0
1
2
3
4
5
6
7
8
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h/
d)
Econsume Ediesel
 
Figure 3-13: Correlation of energy consumption and energy produced by genset 
 
Balance of energy 
Figure 3-14 presents as a brief overview the analysis of energy balance of the PVHS 
with the equation assumptions as described previous section. The daily average 
energy produced by PV is 8.7 kWh, the daily average energy produced by diesel 
generator is 0.6 kWh. The daily average PV energy use is 6.9 kWh. The data shows 
the energy used produced by PV is about 79%.   
 
 
 44
0
2
4
6
8
10
12
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h/
d)
Epv Econsume Epv use Ediesel
 
Figure 3-14:  Balance of energy of the PVHS at SERT 
 
System performance 
The PR of 66.6% indicates that on an annual base under the prevailing conditions 
33.4% of the nominal energy is not available for load supply due to losses in 
reflection, higher module temperature, cable and conversion losses, even if the 
station is continuously used day by day. This potential of the system is comparably 
high to the potential range of PVHS. All performance indicator values from the 
monitor are high. One reason is the high uniformity of the irradiation profile 
throughout the year and the system testing making under controllable load conditions 
(timer load simulator). Hence, the system performance results are probably higher 
than under real loads.    
 
Table 3-1: PVHS performance 
 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave 
Gt (kWh/m2 d) 4.65 5.34 5.47 5.91 5.42 5.31 5.06 5.33 5.48 5.73 5.37 5.33 5.37 
PR (%) 68.2 63.8 62.3 59.5 59.7 67.4 71.7 66.1 71.2 66.4 71.7 70.3 66.6 
FY (h/d) 3.5 3.6 3.6 3.5 3.6 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 
ηpv (%) 10.1 9.9 9.7 9.6 9.7 9.9 10.1 10.0 10.1 10.0 10.2 10.2 9.9 
Fsol (%) 96.6 98.1 98.0 98.0 98.2 96.0 96.1 96.2 95.6 96.6 94.7 95.9 96.7 
 
 
 
 
 45
4 RURAL ELECTRIFICATION SOFTWARE  
 
One problem of rural electrification is the difficulty in selecting a suitable technology 
for the target area. The two parameters technical performance and economic 
performance are often used as indicators in the evaluation process. In order to 
evaluate and identify the proper power system technology for rural area application, 
simulation software called “Rural Electrification System (RES)” is developed for this 
purpose. RES is developed by the School of Renewable Energy Technology, 
Naresuan University, in the framework of MGCT projects [Ketjoy, 2003]. 
 
4.1 Software concept 
 
RES is a sizing, simulation and economic analysis tool for both renewable energy 
and conventional energy technology applications. Renewable technology consists of 
PV-Diesel Hybrid System (PVHS), Stand-alone PV Station (PVS), Solar Home 
System (SHS) and Centralized PV Battery Charging Station (BCS). Conventional 
technology consists of Stand-alone Diesel Generator Station (DGS) and Grid 
Extension (GE). The technical result shows all energy data which are useful when 
used for comparison with other system types. The economics result shows net 
present value, life cycle costs and levelized costs of each system which the user can 
use to compare with another system technology. This software can offer highly 
accurate results based on the actual meteorological database input by the user for 
each area. This software serves as a useful tool for energy planners and system 
designers when selecting the most appropriate rural electrification option and offering 
the most optimal technical and economic benefits for the people living in rural areas. 
 
This software offers a graphic user interface that is simple and easy to understand. 
All system components are stored in different libraries to minimize input time by the 
user. More than 120 models of PV modules from several manufacturers are already 
included in the database of the software. Integrated help files together with step by 
step instructions given during the execution of the program ensures that the RES 
software is a self-learning and user-friendly application tool. 
 
RES provides a wide range of energy supply systems which are already present in its 
software libraries. The software is divided into two main modules: renewable energy 
 46
system and conventional energy system, with their associated sub modules as show 
in Figure 4-1. All systems can simulate both technical and economic performances 
except the grid extension sub module which only can simulate economic analysis 
[Ketjoy, 2003]. 
 
RES
Renewable Energy
System
Conventional Energy
System
PV-Diesel
Hybrid System
PV
Standalone
System
Solar Home
System
Battery
Charging
System
Diesel
Generator
Grid
Extension
System &
Economic
Analysis
System &
Economic
Analysis
System &
Economic
Analysis
System &
Economic
Analysis
Economic
Analysis
System &
Economic
Analysis  
 
Figure 4-1: Structure of the RES 
 
 
4.2 Model and algorithms 
 
This section describes the various algorithms used to calculate, on a month-by-
month basis, the energy production of PV systems in RES. A flowchart of the 
algorithms is shown in Figure 8-1 to Figure 8-6 (Appendix B). The basis of solar 
energy is covered in Section 4.2.1, which describes the tilted radiation calculation 
algorithm that is common to all renewable energy system models (PVHS, PVS, SHS 
and BCS). It is used to calculate solar radiation in the plane of the PV array, as a 
function of its operation, given monthly mean daily solar radiation on a horizontal 
surface. Section 4.2.2 presents the photovoltaic array model, which calculates PV 
array energy production given ambient temperature and available solar radiation. 
This algorithm is also common to all application models. Then four different 
application models are used to evaluate the interaction of the various components of 
the PV system and predict how much energy can be expected from the PV system 
on an annual basis. Section 4.2.3 presents the economic model, which calculates an 
economic performance (LCC, NPV and COE) of the system. This algorithm is 
common to all six application model (Figure 4-1). A validation of the RES is 
presented in Section 4.3.  
 47
4.2.1 Solar radiation model 
Extraterrestrial radiation on a horizontal surface and clearness index  
Solar radiation at normal incidence received at the surface of the earth is subject to 
variations due to change of the extraterrestrial radiation. The calculation of the 
theoretical possible extraterrestrial radiation is necessary to obtain the ratio of 
radiation level under the atmosphere. It is often necessary for the calculation of daily 
solar radiation to have the integrated daily extraterrestrial radiation on a horizontal 
surface ( 0H ) over the period from sunrise to sunset.  The monthly mean daily 
extraterrestrial radiation, ( 0H ), is a useful quantity [Duffie, 1991]. For latitudes in the 
range of +60 to –60, it can be calculated with Equation (4.1) using n and δ for the 
mean day of the month from Table 4-1. 
 
Table 4-1:  Recommended Average Days for Months and Values of n 
Month Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 
Date 17 16 16 15 15 11 17 16 15 15 14 10 
Day of year 
 (n) 
17 47 75 105 135 162 198 228 258 288 318 344 
 
   

 +×

 +×= δφπωωδφπ sinsin180sincoscos365
360cos033.013600240 SSSC
nGH    (4.1) 
 
Where:   
 GSC  =  Solar constant, 1,376 W/m2 
 n      = The day of the year. 
 δ =  Monthly mean solar declination, Degrees 
 ωS = Sunset hour angle, Degrees 
 φ = Latitude of location, Degrees 
 H     = Monthly mean daily total radiation on horizontal surface, MJ/m2.day 
   0H    = Monthly mean daily extraterrestrial radiation on horizontal surface, MJ/m
2.day 
 
Before reaching the surface of the earth, radiation from the sun is attenuated by the 
atmosphere and the clouds. The ratio of solar radiation at the surface of the earth to 
 48
extraterrestrial radiation is called the clearness index. Thus the monthly average 
clearness index, TK , is defined as: 
   
                  
0H
HKT =  (4.2) 
 
Where TK  values depend on the location and the time of year considered; they are 
usually between 0.3 (for very overcast climates) and 0.8 (for very sunny locations). 
 
Calculation of hourly global and diffuse irradiance 
Solar radiation can be divided into two components: beam or direct radiation, which 
is radiated from the sun to earth surface directly, and diffuse radiation, which is 
reflected and/or scattered by small matter in the atmosphere such as clouds or water 
drops, then to the earth surface [Duffie, 1991/RETScreen, 2003].  
 
Monthly average daily diffuse radiation dH  is calculated from monthly average daily 
global radiation H  using the equation (4.3): 
 
            32 137.2189.4560.3391.1 TTTd KKKH
H −+−=  (4.3) 
 
When the sunset hour angle for the average day of the month is less than 81.4°, and: 
 
            32 821.1427.3022.3311.1 TTTd KKKH
H −+−=  (4.4) 
 
When the sunset hour angle is greater than 81.4° (the monthly average clearness 
index, TK  is calculated trough equation (4.2). 
  
Then, average daily radiation is then broken down into hourly values. This is done 
with the formula from Collares-Pereira and Rabl for global irradiance.   
 
 49
           ( )
S
S
S
St
t baH
Ir
ωπωω
ωωωπ
cos
180
sin
coscoscos
24 −
−+==  (4.5) 
           a = 0.409 + 0.5016sin(ωS – 60) (4.6)  
           b = 0.6609 + 0.4767sin(ωS – 60) (4.7) 
 
Where:             
 rt = Ratio of hourly total radiation to daily total radiation 
 tI  = Hourly mean total radiation on horizontal surface, MJ/m
2.h 
 ω = Hour angle, Degrees 
 
The formula from Liu and Jordan for diffuse irradiance: 
 
              
S
S
S
S
d
d
d H
Ir
ωπωω
ωωπ
cos
180
sin
coscos
24 −
−==                          (4.8) 
Where: 
 rd = Ratio of hourly diffuses radiation and daily total diffuse radiation 
 dI  = Hourly mean diffuse radiation on horizontal surface, MJ/m
2.h 
 
Correlation between hourly total, beam and diffuse radiation is: 
 
               dbt III +=                                               (4.9) 
  
Where: 
 tI  = Hourly mean total radiation on horizontal surface, MJ/m
2.h 
    bI  = Hourly mean beam radiation on horizontal surface, MJ/m
2.h 
    dI  = Hourly mean diffuse radiation on horizontal surface, MJ/m
2.h 
 
Radiation on a tilted surface and its estimation  
Hourly radiation on a tilted surface is given by: [Duffie, 1991] 
 
              

 −+

 ++=
2
cos1
2
cos1 βρβ gtdbbT IIRII                 (4.10) 
 50
Where: 
 IT = Hourly mean diffuse radiation on tilted surface, (MJ/m2.h) 
 β = PV array tilted angle, Degrees 
 ρg = Ground albedo (0.2 for non-snow cover) 
 
Ratio of beam radiation on PV array tilted surface to that on horizontal surface 
determined by: [Duffie, 1991] 
 
   δφωδφ
ωγβδωγβφδ
ωβφδγβφδβφδ
θ
θ
sinsincoscoscos
sinsinsincoscoscossinsincos
coscoscoscoscossincossincossinsin
cos
cos
+
++
+−
==
z
bR    (4.11)  
 
Estimation of Ambient Temperature 
The ambient temperature can be estimated by using the sinusoidal ambient 
temperature model which is based on the variation of maximum and minimum 
ambient temperatures in a day [Ketjoy, 1999].  
 
              ( ) ( ) ( ) 

 

−++= tTTTTtTamb 24
2sin
2
1
minmaxminmax
π              (4.12) 
Where: 
 Tamb(t) = Ambient temperature at time, t 
 Tmax  = Maximum ambient temperature of the day 
 Tmin  = Minimum ambient temperature of the day 
 t  = h – 9  
 h   = Considered time in unit of hour 
 
4.2.2 System component model 
PV Generator 
A photovoltaic generator is the whole assembly of solar cells, connections, protection 
parts, supports etc. This section presents the model focusing only on 
cell/module/array. Steps in calculation of PV module current, under certain operating 
conditions are presented below [Hansen, 2000/ Castañer, 2002]:  
 
 51
 ( )PMSM
M
C
NN
P
P ×=
0max,
0max,  (4.13) 
 
SM
M
OCC
OC N
V
V 0,0, =  (4.14) 
 
PM
M
SCC
SC N
I
I 0,0, =  (4.15) 
 
e
mkTV
C
C
t
0
0, =  (4.16) 
 C
t
C
OC
OC V
V
v
0,
0,
0, =  (4.17) 
 
( )( )
( )1
72.0ln
0,
0,0,
+
+−=
OC
OCOC
v
vv
FF  (4.18) 
 ( )CSCCOC
C
IV
P
FF
0,0,
0max,
0 ×=  (4.19) 
 
0
1
FF
FFrs −=  (4.20) 
 C
SC
C
OCsC
S I
Vr
R
0,
0,×=  (4.21) 
Where: 
 CP 0max,  = Maximum power for the cell 
 MP 0max,  = Maximum power to the module 
 COCV 0,  = Open circuit voltage for the cell 
 MOCV 0,  = Open circuit voltage for the module 
 CSCI 0,  = Short circuit current for the cell 
 MSCI 0,  = Short circuit current for the module 
 SMN  =  Number of cells in series 
 PMN  = Number of cells in parallel 
 CtV 0,        = Thermal voltage in the semiconductor of a single solar cell at STC 
 m  = Idealising factor 
 k  = Boltzmann’s constant, k = 1.381 x 10-23 J/K 
 52
 CT0        = Cell temperature at standard condition = 25 
oC 
 e  = Electron charge e = 1.602 x 10-19 C 
 0,OCv  = Open circuit voltage 
 FF  = Fill factor 
 0FF  = Fill factor at standard condition 
 sr  = Series resistance 
 CSR  = Equivalent serial resistance of the cell 
 
Cell Parameters for operating conditions 
 
 
0,
0,
1
a
C
SC
G
I
C =  (4.22) 
 a
C
SC GCI ⋅= 1  (4.23) 
 aa
C GCTT ⋅+= 2  (4.24) 
 ( )CCCOCCOC TTCVV 030, −+=  (4.25) 
 ( )
e
TmkV
C
C
t
+= 273  (4.26) 
Where : 
 2C  = Constant, 2C = 0.03 Cm
2/W 
 3C  = Constant, usually considered to be 3C = –2.3 mV/
 oC 
 0,aG  = Irradiation, W/m
2 
 aG  = Ambiant irradiation, W/m
2 
 aT  = Ambient temperature, 
oC 
 CT  = Working temperature of the cell 
 
Module current for operating conditions 
 
           
  − +    = −      
M C M C SM
SM OC S
M C PM
PM SC C
SM t
NV N V I R
NI N I 1 exp
N V
 (4.27) 
 53
Where: 
 MI  = Total generated current by the module 
 MV        = Applied voltage at the module’s terminals 
     
Table 4-2: Nominal and Standard conditions 
Nominal conditions Standard conditions 
Radiation: refaG , = 800 W/m
2 Irradiation: refaG , = 1000 W/m
2 
Ambient temperature : refaT , = 20 °C Cell temperature : CT0 = 25 °C 
 
Array current for operating conditions 
 
 ∑
=
= P
M
i
i
A II
1
  or   (4.28) 
 MP
A IMI ⋅=  (4.29) 
Where: 
 AI  = Total current of the array 
 PM  = Number of modules in parallel 
 
Power generated by PV array 
 
 AAA VIP ×=  (4.30) 
Where : 
 AP  = Power generated by PV array 
 AI  = Total generated current by the PV array 
 AV  = Applied voltage at the PV array 
 
Note: In order to have a clear specification of which element (cell or module) the 
parameters in the mathematical model regard, the following notation is used from 
now on: the parameters with superscript “M” are referring to the PV module, while the 
parameters with superscript “C” are referring to the solar cell. 
 
 
 
 54
Energy output from Inverter 
The PV arrays produce DC power and therefore when the PV system contains an AC 
load, a DC/AC conversion is required. This is the reason why this section presents 
the inverter model. The inverter is characterized by a power dependent efficiency 
( Invη ). The role of the inverter is to keep on the AC side the voltage constant at the 
rated voltage 230 V and to convert the input power into the output power with the 
best possible efficiency. The inverter model is [RETScreen, 2003/ Manwell, 1998]: 
 
 InvArrayInv EE η×=  (4.31) 
Where 
 InvE  = Energy output from inverter, kWh 
 ArrayE  = Energy generated by PV array, kWh 
 Invη  = Inverter efficiency, % 
 
Charge controller 
This section presents the modeling of the controller of a PV system. The charge 
controller is used to manage the energy flow to PV system, batteries and loads by 
collecting information on the battery voltage and knowing the maximum and minimum 
values acceptance for the battery voltage. The modeling of the controller is presented 
below [RETScreen, 2003/ Manwell, 1998]: 
 
 Chginout EE η⋅=  (4.32) 
Where : 
 outE  = Energy output from charge controller, kWh 
 inE  = Energy input to charge controller, kWh 
 Chgη  = Efficiency of charge controller 
 
Battery 
An important element of a PV system is the battery. The battery is necessary in such 
a system because of the fluctuating nature of the output delivered by the PV arrays. 
Thus, during the hours of sunshine, the PV system is directly feeding the load, the 
excess electrical energy being stored in the battery. During the night, or during a 
 55
period of low solar irradiation, energy is supplied to the load from the battery. The 
steps of battery model as used in the RES are presented as followed [RETScreen, 
2003/ Manwell, 1998]: 
 
Minimum Energy Left in Battery 
 
 BattCapDODE maxBattMin ×−= )1(  (4.33) 
Where:  
 BattMinE  = minimum energy left in battery, kWh 
 maxDOD  = maximum depth of discharge of battery, % 
 BattCap  = battery capacity, kWh 
 
Maximum Discharge Energy of Battery  
 
 ( )BattInvBattBattMinBattMaxDis EEE ηη ××−= )(  (4.34) 
Where: 
 MaxDisE  = Maximum discharge energy of battery, kWh  
 BattE  = Energy of battery, kWh 
 Battη  = Battery efficiency, % 
 BattInvη  = Battery inverter efficiency, % 
 
Discharge Energy of Battery  
 
 InvLoadBattDis EEE −=  (4.35) 
Where: 
 BattDisE  = Discharge energy of battery, kWh 
 LoadE  = Required energy for load, kWh 
 
Energy Used for Charge the Battery 
 
 ( ) BattBattInvLineChgBatt EE ηη ××=  (4.36) 
 56
Where : 
 ChgBattE  = Energy used for charge battery, kWh 
 LineE  = Energy in line after supplied to load, kWh 
 
Energy of Battery After charge 
 
 ChgBattCBattOldCBattNew EEE += )()(  (4.37) 
Where: 
 )(CBattNewE  = Energy of battery after charge, kWh 
 )(CBattOldE  = Energy of battery before charge, kWh 
 
Energy of Battery after Discharge 
 
 



×−= BattBattInv
BattDis
DBattOldDBattNew
EEE ηη)()(  (4.38) 
Where: 
  )(DBattNewE  = Energy of battery after discharge, kWh 
 )(DBattOldE  = Energy of battery before discharge, kWh 
 
Battery State of Charge  
 
 
BattCap
ESOC Batt=  (4.39) 
Where: 
 SOC  = Battery State of Charge, % 
  BattE  = energy of battery, kWh 
 BattCap  = battery capacity, kWh 
 
Diesel generator and surplus energy  
Conventional generators are normally diesel engines directly coupled to generators. 
The frequency of the AC power is maintained by a governor on one of the engines. 
The governor adjusts the flow of fuel to the engine to keep the engine and generator 
 57
speed essentially constant. The grid frequency is directly related to the speed of the 
generator, and is, therefore, maintained at the desired level. The RES diesel 
generator model uses the net loads energy demand to calculate energy supplied by 
the diesel generator for a base case and additional system configurations. The 
energy flow model of the diesel generator as used in RES is [RETScreen, 2003/ 
Manwell, 1998]: 
 
Energy Generated by Diesel Generator 
 
 DieselDiesel DieselCapE η×=  (4.40) 
Where: 
    DieselE           = Energy Generated by Diesel Generator, kWh 
 DieselCap   = Diesel generator capacity, kWh 
 Dieselη  = Diesel generator efficiency (20 - 40), % 
 
Surplus Energy 
 
 BattCapEE BattSurplus −=  (4.41) 
Where: 
 SurplusE  = Surplus energy, kWh 
 BattE  = Energy of battery, kWh 
     BattCap  = Battery capacity, kWh 
 
4.2.3 Economical model 
The basis of most engineering decisions is economics. Designing and building a 
device or system that functions properly is only part of the engineer’s task. The 
device or system must, in addition, be economic, which means that the investment 
must show an adequate return.   
 
The economics section of the RES model is based on the use of conventional life 
cycle costing economics. That is, the RES economic routine performs a first level 
economic evaluation of a PV system. This includes yearly cash flows, the present 
 58
value of system costs, incomes and levelized annual costs. In addition, the analysis 
has been designed to allow for a side-by-side comparison of the economics of a 
hybrid power system with those of a diesel-only powered system and grid extension. 
Another aspect of RES economics is the ability to examine the potential economic 
advantage (or disadvantage) of adding renewable energy sources to a pre-existing 
diesel-powered system. It is assumed that the user will use the RES economics 
package to obtain a desired system design and then will perform an independent 
economic analysis using the methods and software of his or her choice. 
 
Total Capital Cost 
As detailed below, the cash flow analysis produces year-by-year detailed figures for 
project incomes and disbursements. The disbursements are separated into the 
following categories: installed capital costs/annuity payments, fuel costs, operation 
and maintenance expenses, and equipment replacement costs. 
 
Installed Capital Cost is the initial venture capital for a PV system including 
equipment costs, installation expenses, tariffs, shipping costs, and possibly the cost 
of extending a distribution network from the PV power system to the consumer loads. 
While every effort has been made to identify the major capital costs, RES uses a 
“balance of system” term, CCap,BOS, in order to account for any capital costs which are 
unique to the user's application. Therefore the system installed capital cost, CCap,tot is 
given by [Stoecker, 1989/Manwell, 1998/Yaron, 1994]: 
 
   OthCapInstCapBOSCapBattCapDieselCapInvCapPVCaptotCap CCCCCCCC ,,,,,,,, ++++++=  (4.42) 
 
Where: 
               DieselInstBattInstBattInvInstInvInstBattInstPVInstInstCap CCCCCCC ,,,,,,, +++++=   (4.43) 
         ChgCapBattInvCapInvCapInvCap CCCC ,,,, ++=  (4.44) 
         OthShipOthCap CCC +=,  (4.45) 
 
Where: 
 CCap,PV = Capital cost of PV array, Currency 
 CCap,Inv = Capital cost of inverter, Currency 
 59
     CCap,Diesel = Capital cost of diesel generator, Currency 
 CCap,Batt = Capital cost of battery storage, Currency 
 CCap,Inst = Installation cost, Currency  
 CCap,Oth = Capital cost of other, Currency 
 CShip = Shipping cost, Currency  
 
Annual Cost 
These consist of regular maintenance costs, fuel cost (diesel generator) over the 
years. The actual data of annual maintenance and fuel cost on systems installed is 
difference for each location. Therefore the system annual cost model of RES, Cann,tot 
is given by [Manwell, 1998/Yaron, 1994]: 
 
      OthannFuelannSysannDieselannInvannBattannPVanntotann CCCCCCCC ,,,,,,,, ++++++=  (4.46) 
 
Where: 
 DieselLFuelFuelann HrpFuelConsumCC ××= /,   (4.47) 
           ChgannBattInvannInvannInvann CCCC ,,,, ++=  (4.48) 
 
Where Cann,Fuel is annual cost of fuel, FuelConsump is diesel engine fuel consumption 
rate and HrDiesel is hour operation of the diesel generator. 
 
Replacement Cost 
Replacement costs are slightly more complex in that they involve regular cash 
payments but are not truly annual. The main components of the system have to 
replace during the life time of the system. In order to convert replacements costs into 
annual ones therefore the replacement annual cost (CRepl) equation is given by 
[Manwell, 1998/Yaron, 1994]: 
 
 ( )niPWFCC OHDieselRepl ,,, ×=  (4.49) 
 ( )niPWFCC BattBattRepl ,,, ×=  (4.50) 
 ( ) ( )niPWFCCCC ChgBattInvInvInvRepl ,,, ×++=  (4.51) 
 ( )niPWFCC OthOthRepl ,,, ×=  (4.52) 
 60
 OthReplInvReplBattReplDieselRepltotRepl CCCCC ,,,,, +++=  (4.53) 
 
Where:  ( ) 


+= niFPWF 1
1  (4.54) 
 
f
fii f +
−=
1
    (4.55)                      
Where: 
 PWF = Present-worth factor 
 F = Future money, Currency 
 n = Component Lifetime, Year 
 i = Actual interest rate, % per year 
 if = Interest rate, % per year 
 f = inflation rate, % per year 
 
Present value of the annualized cost and salvage value 
The series-present-worth factor (SPWF) translates the value of a series of uniform 
amounts C into the present worth. The present worth of the series can be found by 
applying the PWF to each of the C amount [Manwell, 1998/Yaron, 1994]: 
  
 ( )( )niSPWFCC totannPWann ,,,, ×=  (4.56) 
 ( )( ) 



+
−+= n
n
ii
iASPWF
1
11    (4.57)         
 ( )niPWFCC SalPWSal ,,, ×=  (4.58) 
                     
Where A is annual money (Currency), n is system lifetime (Years) and Csal is salvage 
value.            
 
Life Cycle Cost (LCC) 
The methodology used to define the LCC is a multi-step process, as present above. 
This process requires sets of data from fielded systems and the development of a 
sophisticated database tool for analysis of the data. LCC determine which power 
supply systems can be cost-competitive with other energy options [Manwell, 
1998/Yaron, 1994].  
 61
 PWSalPWReplPWanntotCap CCCCLCC ,,,, −++=  (4.59) 
 
Net Present Value (NPV) 
In the RES economics, the net present value of the project is determined from 
summing the annual cost, replacement cost and the initial capital expenses 
[Stoecker, 1989/Manwell, 1998/Yaron, 1994]. 
 
 ( ) PWReplPWanntotCap CCCNPV ,,, ++−=  (4.60) 
 
Levelized Cost of Energy (COE) 
Another levelized calculation concerns the cost of energy, COE. The total levelized 
cost of energy is given by [Manwell, 1998/Yaron, 1994]: 
 
 ( )SysLifeE
LCCCOE
Prod ×
=  (4.61) 
 
Where ProdE  is energy that system generated in one year (kWh/y) and SysLife  is 
system lifetime (years). 
 
4.3 Software testing 
 
This section presents two example of validation against monitored data from a real 
site. The example is a system test and compares the predicted energy production of 
a PVHS at SERT and PVS at Chiangria Province, Thailand the RES model against 
results of monthly average data from the sites.     
 
4.3.1  Validation of RES PVHS model compared with SERT PVHS monitored 
In this section the predictions of the RES PVHS model are tested against monitored 
data from real sites. The system configurations of PVHS already mention in Chapter 3. 
Titled solar radiation is shown in Table 4-3.  
 
 
 
 
 62
Table 4-3: Comparison of RES PVHS calculation and SERT PVHS monitored  
Tilted Solar Radiation 
(kWh/m2.d) 
PV Energy Production 
(kWh) 
Genset Energy 
Production (kWh) Month 
Monitored Simulation 
% 
error 
Monitored Simulation 
%  
error 
Monitored Simulation 
% 
error 
Jan 4.65 5.18 -11 267 275 -3 19 21 -12 
Feb 5.34 5.61 -5 257 282 -10 15 16 -5 
Mar 5.47 5.73 -5 284 296 -4 17 18 -9 
Apr 5.91 6.00 -2 283 310 -10 14 15 -9 
May 5.42 6.01 -11 287 312 -9 17 19 -11 
Jun 5.31 5.19 2 279 274 2 20 22 -10 
Jul 5.06 4.89 3 261 257 2 22 25 -13 
Aug 5.33 5.31 0 283 281 1 19 20 -8 
Sep 5.48 4.89 11 293 251 14 22 23 -5 
Oct 5.73 5.27 8 305 270 12 20 22 -12 
Nov 5.37 4.82 10 281 250 11 21 23 -8 
Dec 5.33 4.98 7 283 261 8 23 24 -7 
Year 5.37 5.32 1 3,362 3,319 1 227 248 -9 
 
For RES, monthly results were obtained by exporting hourly simulation data and 
performing a summation. The results of the comparison are summarized in Table 4-3. 
On an average yearly basis RES predicts slightly less titled solar radiation than 
monitored data (5.37 vs. 5.32 kWh/m2.d, or a difference of 1%). Part of this difference 
(around 1%) is attributable to differences in the calculations of PV energy production, 
as shown in the table. Contributions from the genset, reported in table as yearly 
energy production, differ around 9% (227 vs. 248 kWh). Overall, these differences 
are insignificant and illustrate the adequacy of the RES PVHS model for feasibility 
studies. Graphical comparisons of the results are present in Figure 4-2 to Figure 4.4. 
   
0
1
2
3
4
5
6
7
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Ti
lte
d 
So
la
r R
ad
ia
tio
n 
(k
W
h/
m
2 .d
)
Monitored Simulation
 
Figure 4-2: Comparison of titled solar radiation calculated by RES and monitored 
 63
0
50
100
150
200
250
300
350
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
PV
 E
ne
rg
y 
Pr
od
uc
tio
n 
(k
W
h)
Monitored Simulation
 
Figure 4-3: Comparison of PV energy production calculated by RES and monitored 
 
0
5
10
15
20
25
30
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
G
en
se
t E
ne
rg
y 
Pr
od
uc
tio
n 
(k
W
h)
Monitored Simulation
 
Figure 4-4: Comparison of genset energy production calculated by RES and monitored 
 
4.3.2 Validation of RES PVS model compared with Chiangria PVS monitored 
In this section the predictions of the RES PVS model are tested against monitored 
data from real sites. The PVS located Northern of Thailand in Chiangria Province 
(latitude 20 °N). Titled solar radiation is shown in Table 4-4.  
 
 64
A
C
 B
us 230 V
 50/60 H
z
LOAD
SB
~
PV
SIBB
Solar radiation
Gt
Ta
Tc
kWh
Epv use
~
 
 PV: PV generator “Siemens SP 75”, 75W @ 40 modules 
 BB: Battery bank “SunGel 2SG650”, 60V @ 650 Ah 
 SB: Grid connected inverter “SMA Sunny Boy”, 3.0 kW 
 SI: Battery inverter “SMA Sunny Island”, 3.3 kW 
  
Figure 4-5: PV system at Chiangria Province, Thailand 
 
The system specifications consisting of (Figure 4.5): 3 kWp PV generators, the array 
is titled at 20° facing south. 3.0 kW Sunny Boy grid inverter 90% average efficiency, 
3.3 kW Sunny Island battery inverter (bi-directional inverter) 90% average efficiency 
and 39 kWh SunGel battery storage with 80% round trip efficiency and 40% 
maximum depth of discharge (DOD). The overhead distribution line is 420 m service 
line. Total energy demand is approximately 8.9 kWh/d. 
 
Table 4-4: Comparison of RES PVS calculation and Chiangria PVS monitored  
Tilted Solar Radiation 
(kWh/m2.d) 
PV Energy Production 
(kWh) Month 
Monitored Simulation 
%  
error 
Monitored Simulation 
%  
error 
Jan 4.79 4.54 5 432 398 8 
Feb 5.52 4.97 10 453 411 9 
Mar 5.79 5.23 10 484 472 3 
Apr 6.01 5.71 5 495 472 5 
May 5.98 5.91 1 491 471 4 
Jun 5.20 5.11 2 443 414 7 
Jul 4.91 4.64 5 435 405 7 
Aug 5.30 5.11 4 450 437 3 
Sep 4.91 4.59 7 433 405 6 
Oct 5.36 4.68 13 449 443 1 
Nov 4.96 4.13 17 436 398 9 
Dec 4.73 4.23 11 428 394 8 
Year 5.29 4.90 7 5,429 5,121 6 
 
The results of the comparison are summarized in Table 4-4. On an average yearly 
basis RES predicts slightly less titled solar radiation than monitored data (5.29 vs. 
4.90 kWh/m2.d, or a difference of 7%). Part of this difference (around 6%) is 
 65
attributable to differences in the calculations of yearly PV energy production, as 
shown in the table (5,429 vs. 5,121 kWh). Overall, these differences are insignificant 
and illustrate the adequacy of the RES PV model for feasibility studies. Graphical 
comparisons of the results are present in Figure 4-6 to Figure 4.7. 
 
0
1
2
3
4
5
6
7
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Ti
lte
d 
So
la
r R
ad
ia
tio
n 
(k
W
h/
m
2 .d
)
Monitored Simulation
 
Figure 4-6: Comparison of titled solar radiation calculated by RES PVS and monitored 
 
 
0
100
200
300
400
500
600
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
PV
 E
ne
rg
y 
Pr
od
uc
at
io
n 
(k
W
h)
Monitored Simulation
 
 
Figure 4-7: Comparison of PV energy production calculated by RES PVS and monitored 
 
 66
4.4 Summary 
 
In this section the algorithms used by the RES have been shown detail. The titled 
irradiance calculation algorithms, the PV array model and the economic model are 
common to all applications. The titled irradiance calculation uses an hourly model. 
The PV array model takes into account changes in array performance induced by 
ambient temperature. The PVHS, PVS, SHS, BCS, DGS and GE model are relative 
energy flow models based on assumed average efficiencies and are relative 
economic models based on life cycle cost analysis. The Renewable Energy System 
model is more complex and allows for distinction between similar and custom 
difference loads profile which may have an influence on the amount of energy going 
through the battery. The validations of RES illustrate the adequacy for Rural 
Electrification System feasibility studies.    
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 67
5 CASE STUDY OF RURAL ELECTRIFICATION IN MEKONG COUNTRIES 
 
5.1 Introduction 
 
The case study of rural electrification in Mekong Countries presents how an energy 
planner/engineer can make a quick pre-feasibility study on remote area power supply 
using the software RES (Chapter 4). The system performance, economic 
performance and sensitivity analysis are presented of three different locations from 
selected Mekong Countries. In this research the PV system analysis limited at 10 
kWp cause from not available actual data of higher installed capacity for 
validation of study results.    
 
Ban Pang Praratchatang (BPP) in Thailand, Samaki in Cambodia and Thapene in 
Lao PDR have been selected as cases for this pre-feasibility analysis, because 
relevant literature for pre-electrification with PV systems is available. BPP was 
selected because there has been a development project with a PV system and 
monitoring data is available form this system under the framework of MGCT project 
[Ketjoy, 2004]. Samaki was selected because there has been a development project 
with a PV system and monitoring data is available form this system under the 
Ministry of Industry, Mines and Energy (MIME) project [Li, 2002] and Thapene was 
chosen because there has available data from SERT and CORE.  
 
5.2 Case of Ban Pang Praratchatang, Thailand 
 
5.2.1 Description of Ban Pang Praratchatang  
Location and renewable energy resources 
Ban Pang Praratchatang is a hill-tribe village as part of Doi Tung Development Royal 
Project in the Mae Fah Luang district of the Chiang Rai province located in the 
northern part of Thailand (Figure 5-1). This area encompasses a total of 27 village 
communities of different ethnic minority groups and hill-tribes; Akha, Lahu, Tai Yai 
and ethnic Chinese immigrants continue to perform ancient rituals and celebrate 
traditional folk festivals throughout the year. With many aspects of their culture and 
way of life well preserved, these ethnic communities are of immense ethnographic 
interest and importance to the study and preservation of the rich cultural heritage of 
Asia. Access to education, vocational training and a range of employment 
 68
opportunities this enables ethnic minority groups in the project area to preserve their 
heritage whilst progressing into modernity [Doi Tung].  
 
 
[Source: www.un.org/Depts/Cartographic/map/] 
Figure 5-1: Map of Thailand and location of BPP in Chiang Rai province  
 
They earn a steady income and have become self-sufficient. As a result, there has 
been a substantial improvement in their standard of living and quality of life. The 
village communities have managed to achieve a level of sustainable development 
that fosters the harmonious co-existence of indigenous culture and the surrounding 
natural environment.  
Ban Pang Praratchatang 
 69
Renewable energy resources in BPP have been analyzed as to solar irradiation and 
wind speeds (Table 5-1). Irradiation is quite high with an average value of 4.91 
kWh/m2.d [DEDP, 2000]. In order to run wind turbines efficiently economically, the 
average wind speed should exceed 6 m/s. Wind speeds at BPP reach an average of 
2.6 m/s [DEDP, 2001] and are thus too low for installing wind turbines. As a result, 
solar irradiation is considered the only renewable energy source. 
 
Table 5-1: Renewable energy resource in BPP 
Irradiation in BPP (kWh/m2.d) 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave 
4.24 4.79 5.25 5.86 6.19 5.46 4.85 5.46 4.58 4.58 4.32 4.18 4.91 
Wind speeds (m/s) 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave 
2.8 2.6 3.6 2.8 3.6 3.0 2.5 2.0 1.8 1.5 2.0 2.5 2.6 
 
Load demand of BPP 
The BPP case study is especially suitable to show the trend of electricity demand in 
small hill-tribe villages with the potential to expand to big village in the future. Present 
and future electricity demands have been observed by SERT staff [Rakwichian et al, 
2004]. For the evaluation of RES, only the present electricity demand will be taken 
into consideration.  
Village entrance
20.50 m
20 m
10.20 m
10.60 m
17.80 m
26 m
21.70 m
17.50 m
6.50 m
20.70 m
18.50 m
5.60 m
18.80 m
18 m19.50 m
21.50 m
19.40 m
13 
m
19.50 m
24.50 m
23 m
22.30 m
PVS
Scale 1:1000
House
PCU/Battery house
Pole
Main cable
Service cable
Symbol
N
 
Figure 5-2: Map of BPP village [Rakwichian et al, 2004] 
 70
BPP has about 22 households with 140 inhabitants (Figure 5-2). Income currently 
comes from work as employees under the Doi Tung Development Royal Project. In 
1999, the village was electrified by the Public Work Division (PWD) with 5 strings of 
BCS with a total installed capacity of 750 Wp (150 Wp/string). In 2002, PWD  
installed 3,000 Wp PVS [Rakwichian et al, 2004].  
 
Table 5-2: Load demand and duration time of used in BPP during Monday - Friday 
Appliance Power 
(W) 
Quantity
(Unit) 
Total power
(W) 
Duration 
(Hr) 
Consumption 
(Wh/d) 
Fluorescent lamp 36 2 72 18.00 - 22.00 288 
Fluorescent lamp 18 40 720 18.00 - 22.00 2,880 
Colour TV14” 60 5 300 18.00 - 22.00 1,200 
Colour TV 20” 82 2 164 18.00 - 22.00 656 
B & W 14” 50 1 50 18.00 - 22.00 200 
Refrigerator 100 1 100 18.00 - 22.00 400 
Tap player 120 3 360 18.00 - 22.00 1,440 
VCD player 48 2 96 18.00 - 22.00 384 
Fan 40 3 120 18.00 - 22.00 480 
Total   1,982 18.00 - 22.00 7,928 
 
 
0
500
1000
1500
2000
2500
1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161
Hour
D
em
an
d 
(W
)
 
Figure 5-3: Weekly demand profile of BPP village generate by RES [Rakwichian et al, 2004] 
 
 71
Table 5-2 shows present loads in BPP. The BCS was not taken into account, 
because it was rarely used after the PVS was installed. There is a non-continuous 
load, the peak load of 1,982 W occurs in the evening 4 hours/d. Figure 5-3 shows 
the load profile in hourly steps for the weekly. The peak load of 1.9 kW occurs in the 
evening hours. The villagers have an agreement together for the period of electricity 
usage. The village leader will turn off the supply switch during the day time and turn it 
on again on 18.00. An average electricity demand is calculated at 7,928 Wh/d 
[Rakwichian et al, 2004].  
 
5.2.2 Input of RES  
The main configuration to be investigated in this case is the typical PVHS. The 
technical and economic parameters of the simulated models of each component are 
summarized as follows: 
 
• PV generator 
Characteristics: SIEMENS modules SP75 with module peak power = 75 (W),  
 ISC = 4.8 (A), VOC = 21.7 (V), VMPP = 17.0 (V), IMPP = 4.4 (A) and  
 β = -0.077 V/°C (75 W x 26 module)  
Orientation: South faced modules with a tilt angle of 20° 
Costs: Investment cost is 3,000 €/kWp, O&M is 0.05 %/year of investment  
 Cost, operating lifetime 20 years  
• Diesel generator 
Characteristics: 5 kW, the lifetime is assumed to be 30,000 hours  
Costs: For 5, 25, 50, 75 and 100 kW rated powers investment costs are equal 
 to 533, 325, 220, 183 and 160 €/kW respectively,  
 Overhaul 15,000 hours, overhaul cost 20% of investment  
 Maintenance cost 3%/year of investment 
 Diesel fuel cost at BPP is 0.4 €/Lit 
• Battery storage 
Characteristics: Exide OPzV 305 batteries (20 kWh), C10= 216 Ah, Volt/cell= 2 (V), 
 ageing  model parameters are: initial capacity (C0) = 100% of the 
 nominal, DOD = 70%, and the end of lifetime is at 80% of the 
 nominal capacity and lifetime is taken to be 8 years 
Costs:  Investment costs = 160 €/kWh, O&M=0.05%/year of investment 
 72
• Power conditioning 
Characteristics: PV inverter, type Sunny Boy with MPP tracking 
 Bi-directional battery converter, type Sunny Island 
 Lifetime is taken to be 12 years 
Costs: Investment cost of the PV-inverter and battery converter are taken 
 to be 720 €/kW and 1155 €/kW respectively 
 O&M is 1.0%/year of investment 
• Balance of system 
Characteristics: AC power-line of 220 V (420 m), inter-bus for communication and 
control  unit and control room 
Costs: investment costs of 15% of the total system investment. 
 Project lifetime of 20 years, discount rate of 5 - 10% 
 
5.2.3 System performance results of PVHS at Ban Pang Praratchatan  
Energy consumption 
The yearly energy demand of this system is 2,798.2 kWh, average daily energy 
demand is 7.7 kWh and the energy produced by diesel-generator over the year is 
45.2 kWh (Figure 5-4). 
 
0
1
2
3
4
5
6
7
8
9
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel
 
 
Figure 5-4: Correlation of daily energy demand and energy produced by diesel-generator 
 
 
 73
Balance of energy 
Figure 5-5 presents, as a brief overview, the simulated energy balance of the PVHS 
at BPP with the RES. The daily average energy produced by PV is 9.4 kWh, the daily 
average energy supplied by the diesel generator is 3.77 kWh. Daily average of net 
energy use from PV is 5.7 kWh and no surplus energy in the system. The data show 
64% of that the energy produced by PV can be used. 
 
0
2
4
6
8
10
12
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel Epv nominal Epv use
 
Figure 5-5: Energy balance of the PVHS at BPP 
 
 
0
10
20
30
40
50
60
70
80
90
100
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
So
la
r F
ra
ct
io
n 
(%
)/P
er
fo
rm
an
ce
 R
at
io
 (%
)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Fi
na
l Y
ie
ld
 (h
/d
)
Solar Fraction (Fsol) Performance Ratio (PR) Final Yield (FY)
 
Figure 5-6: System performance of the PVHS at BPP 
 
 74
System performance 
Figure 5-6 presents the PVHS performance; the PR of 60% indicates that on an 
annual base under the prevailing conditions 40% of the nominal energy is not 
available for load supply due to losses in reflection, higher module temperature, 
cable and conversion losses, even if the station is continuously used daily. The 
annual average Fsol of the system is 78% and FY is 3.1 h/d. This potential of the 
system is comparably high to the potential range of PV hybrid system. One reason is 
the high uniformity of the irradiation profile throughout the year and the good match 
between production and consumption. 
 
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1 24 47 70 93 116 139 162
Hour
Po
w
er
 (W
)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
B
at
te
ry
 S
ta
ge
 o
f C
ha
rg
e
Pdemand Pinv Ppv supply Pbatt supply SOCbatt
 
Figure 5-7: Selected weekly power supply by PV, battery and battery SOC of PVHS at BPP 
 
Figure 5-7 shows the distribution of weekly system availability of the PVHS at BPP. 
The demand load supplied directly by PV (Ppv supply) is about 900 W; the remaining 
load is supplied by battery. The frequency distribution of the Battery Stage of Charge 
(SOC) range in the considered evaluation period moves between 0.30 – 0.80. The 
SOC indicates how often the battery is found in a charge state.  
 
 75
5.2.4 Economics performance results of PVHS at Ban Pang Praratchatan  
In this section, the economic performance study results of the PVHS at BPP are presented. 
The results presented are based on LCC and COE. The difference assumptions of the 
economic parameter are considered. Table 5-3 shows the sums up the cases of different 
of an assuming (case 1-6 is PVHS, case 7 is PVS, case 8 is DGS and case 9 is GE). 
 
Table 5-3: Comparison of the difference assumption of the PVHS economics study 
and PVS, DGS and GE 
Description Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9 
PV investment cost (€/kW) 3,000 3,000 3,000 2,600 2,600 2,600 3,000 - - 
Diesel generator (€/kW) 400 400 400 400 400 400 - 400 - 
Battery storage (€/kWh) 160 160 160 140 140 140 160 - - 
Power conditioning (€/kW) 1,007.2 1,007.2 1,007.2 732 732 732 1,007.2 - - 
Grid extension (€/km) - - - - - - - - 14,000 
Transformer (30 kVA) - - - - - - - - 600 
BOS (%of investment cost) 15 15 15 17 17 17 10 50 5 
O&M (%of investment cost) 16 16 16 19 19 19 4 196 3 
Replacement cost (%of 
investment cost) 
30 30 30 27 27 27 34 20 5 
Interest rate (%) 5 7.5 10 5 7.5 10 5 5 5 
Inflation rate (%) 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 
Initial investment cost (€) 18,886 18,886 18,886 16,330 16,330 16,330 15,586 4,000 37,600 
LCC (€) 26,150 24,924 23,914 22,661 21,595 20,722 21,292 13,040 36,300 
COE (€/kWh) 0.60 0.57 0.55 0.52 0.49 0.47 0.61 0.74 0.65 
Note: 1 € = 50 Baht / Import tax = 30% for battery and inverter/ Vat 7% 
 
0.470.49
0.520.55
0.57
0.60 0.61
0.74
0.65
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
40,000
45,000
50,000
Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9
Li
fe
 C
yc
le
 C
os
ts
 (€
)
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
1.00
Le
ve
liz
ed
 C
os
t (
€/
kW
h)
PV array Diesel Power conditioning
Battery BOS O&M
Replacement Grid extension Transformer
COE
 
Figure 5-8: LCC analysis of different assumption 
 76
An analysis of the LCC of the different system assumption is explained in Figure 5-8. 
This figure shows that the LCC of case 1 – 3 the PV array and power conditioning 
represents a basic share in the energy levelized cost. In this case power conditioning 
share is about 20% of the LCC and has a COE of 0.60 – 0.55 €/kWh, caused by the 
high unit cost of (imported components from Europe). In case 4 – 7 cost of power 
conditioning is reduced by 27% by using local components, a COE of 0.52 – 0.47 
€/kWh. These results match the obtained values from actual PV system cost analysis 
of Thailand country [Rakwichian, 2004]. Comparing the PVHS COE, the result shows 
that PVHS has a more attractive COE than PVS and GE. In this case, it shows a very 
attractive COE of DGS. The DSG gives a higher COE when the surplus energy is 
taken into account. Surplus energy from DGS is almost 1.3 times the daily energy 
demand of the system, which means energy lost is 3,578 kWh/y.  
 
5.3 Case of Samaki, Cambodia 
 
5.3.1 Description of Samaki  
Location and renewable energy resources 
Samaki village is in the Prey Nop district of the Kompong Som province (Sihanouk 
Ville). Samaki is a remote village located on the Kompong Smach River, 5 km from 
Viel Reng market (Figure 5-9). The village is unlikely to have immediate access to 
grid electricity, and the access road to the village is usually badly affected during the 
rainy season. There are 40 households in the village, with a population of about 200. 
The average yearly family income is approximately 320 €, and almost all the income 
comes from agriculture and fishing. The villagers generally use kerosene and fuel 
wood for lighting. Certain households with commercial activities, and those who have 
higher incomes, use batteries for lighting, watching television and listening to the 
radio. For recharging the batteries, they carry the batteries to the nearest charging 
station, which costs 1,000 Riels (approximately 0.20 €) for one cycle of recharging. 
Usually one charge can last five days of use. 
 
Renewable energy resources in Samaki have been analyzed as only solar irradiation 
(Table 5-4). Irradiation is quite high with an average value of 5.1 kWh/m2.d [Li, 2000]. 
As a result, solar irradiation is considered the only renewable energy source for the PVHS. 
 
 77
Table 5-4: Solar energy resource in Samaki 
Irradiation in BPP (kWh/m2.d) 
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave 
4.9 5.1 5.9 5.9 5.5 4.9 5.1 4.9 4.8 4.5 4.3 4.9 5.1 
 
 
 
 
Figure 5-9: Map of Cambodia, PV system installed and location of Samaki village [Li, 2002] 
 
Load demand of Samaki 
The Samaki case study is especially suitable for showing the trend of electricity 
demand in poor villages that might expand to big village in the future. Present and 
future electricity demands have been observed by the MIME staff [Li, 2000]. For the 
evaluation of RES, only the present electricity demand will be taken into 
consideration. There is a non-continuous load; a peak load of about 1,600 W occurs 
in the evening 4 hours/d. Figure 5-10 shows the load profile in hourly steps for 
weekly. The peak load of 1.6 kW occurs in the evening hours (18.00 – 21.00). An 
average electricity demand is calculated at 7.3 kWh/d. 
 
      Samaki 
 78
0
500
1000
1500
2000
1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161
Hour
D
em
an
d 
(W
)
 
 
Figure 5-10: Weekly demand profile of Samaki village generated by RES 
 
5.3.2  Input of RES  
The main configuration to be investigated in this case is the typical PVHS. The 
technical and economic assumption parameters of the simulated models of each 
component are similar in Section 5.2.2. The component of the PVHS the described 
below: 
 
• PV generator  1.5 kW 
• Diesel generator  5 kW 
• Battery storage  15 kWh 
• Power conditioning 1.5 kW grid inverter / 3.3 kW battery inverter 
 
5.3.3 System performance results of PVHS at Samaki  
Energy consumption 
The annual energy demand of this system is 2,669 kWh, average daily energy 
demand is 7.3 kWh and the energy produced by diesel-generator over the year is 
51.4 kWh (Figure 5-11). 
 79
0
1
2
3
4
5
6
7
8
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel
 
 
Figure 5-11: Correlation of daily energy demand and energy produced by diesel-generator 
 
Balance of energy 
Figure 5-12 presents as a brief overview the simulated energy balance of the PVHS 
at Samaki with the RES. The daily average energy produce by PV is 7.2 kWh, the 
daily average energy supply by diesel generator is 4.5 kWh. Daily average of net 
energy use from PV is 4.9 kWh and no surplus energy in the system. The data shows 
that about 68% of the energy produced by PV can be used. 
 
0
1
2
3
4
5
6
7
8
9
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel Epv nominal Epv use
 
Figure 5-12: Energy balance of the PVHS at Samaki 
 
 80
0
10
20
30
40
50
60
70
80
90
100
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
So
la
r F
ra
ct
io
n 
(%
)/P
er
fo
rm
an
ce
 R
at
io
 (%
)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Fi
na
l Y
ie
ld
 (h
/d
)
Solar Fraction (Fsol) Performance Ratio (PR) Final Yield (FY)
 
Figure 5-13: System performance of the PVHS at Samaki 
 
 
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1 24 47 70 93 116 139 162
Hour
Po
w
er
 (W
)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
B
at
te
ry
 S
ta
ge
 o
f C
ha
rg
e
Pdemand PInv Ppv supply Pbatt supply SOCbatt
 
Figure 5-14: Weekly power supply by PV, battery and battery SOC of the PVHS at Samaki 
 
System performance 
Figure 5-13 presents the PVHS performance; the PR of 64% indicates that on an 
annual base under the prevailing conditions, 36% of the nominal energy is not 
available for load supply due to losses in reflection, higher module temperature, 
 81
cable and conversion losses, even if the station is continuously used daily. The 
annual average Fsol of the system is 67% and FY is 3.3 h/d. The potential of the 
system is comparably high to the potential range of PV hybrid system. One reason is 
the high uniformity of the irradiation profile throughout the year and the good match 
between production and consumption. 
 
Figure 5-14 shows the distribution of weekly system availability of the PVHS at 
Samaki. The demand load supplied directly by PV (Ppv supply) is about 800 W; the 
remaining load is supplied by battery storage. The frequency distribution of the 
Battery SOC range in the considered evaluation period moves between 0.3 – 0.85. 
The SOC indicates how often the battery is found in a charge state.  
 
5.3.4 Economics performance results of PVHS at Samaki  
Table 5-5 shows the summary of the different cases (case 1-6 is PVHS, case 7 is 
PVS, case 8 is DGS and case 9 is GE). 
 
Table 5-5: Comparison of the difference assumption of the PVHS economics study 
and PVS, DGS and GE 
Description Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9 
PV investment cost (€/kW) 3,000 3,000 3,000 2,600 2,600 2,600 3,000 - - 
Diesel generator (€/kW) 400 400 400 400 400 400 - 400 - 
Battery storage (€/kWh) 160 160 160 140 140 140 160 - - 
Power conditioning (€/kW) 1,019 1,019 1,019 737 737 737 1,019 - - 
Grid extension (€/km) - - - - - - - - 14,000 
Transformer (30 kVA) - - - - - - - - 600 
BOS (%of investment cost) 17 17 17 20 20 20 10 55 5 
O&M (%of investment cost) 25 25 25 29 29 29 4 178 3 
Replacement cost (%of investment 
cost) 
30 30 30 27 27 27 34 18 5 
Interest rate (%) 5 7.5 10 5 7.5 10 5 5 5 
Inflation rate (%) 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 
Initial investment cost (€) 16,580 16,580 16,580 14,330 14,330 14,330 13,480 4,000 37,600 
LCC (€) 24,685 23,246 22,101 21,369 20,154 19,182 17,856 8,279 68,026 
COE (€/kWh) 0.69 0.65 0.62 0.60 0.57 0.54 0.75 0.51 1.28 
Note: 1,000 Riels = 0.20 € / Import tax = 30% / Vat 10% 
 
An analysis of the LCC of the different system assumption is explained in Figure 5-15. 
This figure shows that the LCC of case 1 – 3 of the PV array and power conditioning 
represents a basic share in the energy levelized cost. In this case power conditioning 
share about 20% of LCC and has a COE of 0.69 – 0.62 €/kWh, caused by the high 
 82
unit cost of its (imported components from Europe). In case 4 – 7 cost of power 
conditioning is reduced by 27% by using components from neighboring countries, a 
COE of 0.60 – 0.54 €/kWh. These results match the obtained values from actual PV 
system cost analysis of Cambodia country [Li, 2002]. Comparing the PVHS COE, the 
result shows that PVHS has a more attractive COE than PVS and GE. In this case it 
shows a very attractive COE of DGS. The DSG matches power to the loads demand 
of the Samaki better than other power supply system (in this study environment cost 
not taking into account).  
 
0.540.56
0.600.620.65
0.69
0.75
0.51
1.28
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9
Li
fe
 C
yc
le
 C
os
ts
 (€
)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
1.60
Le
ve
liz
ed
 C
os
t (
€/
kW
h)
PV array Diesel Power conditioning
Battery BOS O&M
Replacement Grid extension Transformer
COE
 
Figure 5-15: LCC analysis of different assumption of Samaki 
 
5.4 Case of Thapene, Lao PDR 
 
5.4.1 Description of Thapene  
Location and renewable energy resources 
Thapene Village is located in the Loungphrabang province. Thapene is a remote 
village about 30 km from Loungphrabang near Khuangxi waterfalls (Figure 5-16). 
The village is unlikely to have immediate access to grid electricity, and the access 
road to the village is usually badly affected during the rainy season. There are 50 
households in the village, with a population of about 130. The average yearly family 
income is approximately 256 €, and almost all the income comes from agriculture 
and labour work. The villagers generally use kerosene for lighting. Certain 
 83
households with commercial activities and those who have higher incomes, use pico 
hydro power generation for lighting, watching television and listening to the radio. For 
pico hydro generation, they install the system along the waterfall nearest to their 
household. The investment costs are about 60 €/kW and the expected lifetime about 
5 years [Source: Thapene pico hydro survey by SERT]. In this research pico hydro 
technology not taken in to account.  
 
As mentioned above, renewable energy resources in Thapene have been analyzed 
as only solar irradiation. The annual mean daily global solar radiation in the country is 
in the range 4.50 - 4.70 kWh/m2.d [Douangvilay, 2002].  
 
 
Figure 5-16: Map of Laos, location of Thapene Village in Loungphrabang 
 
Load demand of Thapene 
The Thapene case study is especially suitable for showing the trend of electricity 
demand in poor villages that might expand to big village in the future. Present and 
 84
future electricity demands have been observed by the SERT staff. For the evaluation 
of RES, only the present electricity demand will be taken into consideration. There is 
a continuous load; the peak load of about 5 kW occurs in the evening period.  
 
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
6
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
D
em
an
d 
(k
W
)
 
Figure 5-17: Daily load profile of Thapene village by SERT observation 
 
 
0
1000
2000
3000
4000
5000
6000
1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161
Hour
D
em
an
d 
(W
)
 
Figure 5-18: Weekly load demand profile of Thapene village generate by RES 
 85
Figure 5-17 shows the daily load profile in hourly steps. An average electricity 
demand is calculated at 33.8 kWh/d. Figure 5-18 shows the weekly load profile in 
hourly step generated by RES. 
 
5.4.2  Input of RES  
The technical and economic assumption parameters of the simulated models of each 
component are similar in Section 5.2.2. The components of the PVHS are described 
below: 
 
• PV generator  9 kW 
• Diesel generator  8 kW 
• Battery storage  90 kWh 
• Power conditioning 3 x 3 kW grid inverter / 3 x 3.3 kW battery inverter 
 
5.4.3 System performance results of PVHS at Thapene  
Energy consumption 
The annual energy demand of this system is 12,337 kWh, average daily energy 
demand is 33.8 kWh and the energy produces by diesel-generator over the year is 
195.3 kWh (Figure 5-19). 
 
0
5
10
15
20
25
30
35
40
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel
 
 
Figure 5-19: Correlation of daily energy demand and energy produced by diesel-generator 
 86
Balance of energy 
Figure 5-20 presents as a brief overview the simulated energy balance of the PVHS 
at Thapene with the RES. The daily average energy produced by PV is 41.4 kWh; 
the daily average energy supplied by diesel generator is 16.3 kWh. Daily average of 
net energy use from PV is 29.4 kWh and without any surplus energy in the system. 
The data shows that about 71% of the energy produced by PV can be used. 
 
0
5
10
15
20
25
30
35
40
45
50
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
En
er
gy
 (k
W
h)
Edemand Ediesel Epv nominal Epv use
 
 
Figure 5-20: Energy balance of the PVHS at Thapene 
 
 
0
10
20
30
40
50
60
70
80
90
100
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
So
la
r F
ra
ct
io
n 
(%
)/P
er
fo
rm
an
ce
 R
at
io
 (%
)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Fi
na
l Y
ie
ld
 (h
/d
)
Solar Fraction (Fsol) Performance Ratio (PR) Final Yield (FY)
 
Figure 5-21: System performance of the PVHS at Thapene 
 87
System performance 
Figure 5-21 presents the PVHS performance at Thapene; the PR of 67% indicates 
that on an annual base under the prevailing conditions, 33% of the nominal energy is 
not available for load supply due to losses in reflection, higher module temperature, 
cable and conversion losses, even if the station is continuously used daily. The 
annual average Fsol of the system is 87% and FY is 3.3 h/d. This potential of the 
system is comparably very high to the potential range of PV hybrid system. One 
reason is the high uniformity of the irradiation profile throughout the year and power 
supply match with the load profile of the Thapene. 
 
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
1 24 47 70 93 116 139 162
Hour
Po
w
er
 (W
)
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
B
at
te
ry
 S
ta
ge
 o
f C
ha
rg
e
Pdemand PInv Ppv supply Pbatt supply BattSOC
 
Figure 5-22: Distribution weekly power supply by PV, battery and battery SOC of at Thapene 
 
Figure 5-22 shows the distribution of weekly system availability of the PVHS at 
Thapene. The demand load supplied directly by PV (Ppv supply) about 1,500 W, 
remain load supply by battery storage. The frequency distribution of the Battery SOC 
range in the considered evaluation period moving between 0.3 – 0.85. The SOC 
indicates how often the battery is found in a charge state.  
 
 88
5.4.4 Economics performance results of PVHS at Thapene  
Table 5-6 shows the summary of the cases with different assumptions similar to the 
previous section.  
 
Table 5-6: Thapene comparison of the different assumptions of the PVHS economics 
study and PVS, DGS and GE 
Description Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9 
PV investment cost (€/kW) 3,000 3,000 3,000 2,600 2,600 2,600 3,000 - - 
Diesel generator (€/kW) 400 400 400 400 400 400 - 400 - 
Battery storage (€/kWh) 160 160 160 140 140 140 160 - - 
Power conditioning (€/kW) 948 948 948 705 705 705 948 - - 
Grid extension (€/km) - - - - - - - - 10,000 
Transformer (30 kVA) - - - - - - - - 600 
BOS (%of investment cost) 8 8 8 10 17 17 8 62 1 
O&M (%of investment cost) 11 11 11 13 19 19 1 145 12 
Replacement cost (%of 
investment cost) 
22 22 22 26 27 27 29 15 1 
Interest rate (%) 5 7.5 10 5 7.5 10 5 5 5 
Inflation rate (%) 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 
Initial investment cost (€) 61,115 61,115 61,115 51,920 51,920 51,920 57,815 10,500 202,600 
LCC (€) 80,468 77,355 74,708 68,429 65,785 63,548 71,166 15,650 185,887 
COE (€/kWh) 0.37 0.36 0.35 0.32 0.31 0.30 0.41 0.36 0.75 
Note: 1,000 Kip = 0.1 € 
 
 
0.75
0.36
0.41
0.37 0.36 0.35 0.32 0.31 0.30
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
180,000
200,000
220,000
240,000
Case1 Case2 Case3 Case4 Case5 Case6 Case7 Case8 Case9
Li
fe
 C
yc
le
 C
os
ts
 (€
)
0.00
0.20
0.40
0.60
0.80
1.00
1.20
Le
ve
liz
ed
 C
os
t (
€/
kW
h)
PV array Diesel Power conditioning
Battery BOS O&M
Replacement Grid extension Transformer
COE
 
Figure 5-23: Thapene LCC analysis of different assumption 
 
 
 89
Figure 5-23 shows an analysis of the LCC of the different technology power system 
assumptions. This figure shows that in cases 1 – 3, the PV array and power 
conditioning represent a basic share in the energy levelized cost. In these cases, the 
PV array is about 44% of LCC and power conditioning (imported components from 
Europe) is 29% of LCC and has an average COE of 0.36 €/kWh. In cases 4 – 7, PV 
array share is about 45%, cost of power conditioning is reduced by 26% by using 
components from neighboring countries, and an average COE is 0.31 €/kWh. 
Comparing the PVHS COE, the result shows that PVHS has a more attractive COE 
than PVS and GE. 
 
5.5 Summary and outlook 
 
In this section levelized cost comparisons for PVSH, PVS, DGS and GE technologies 
were conducted for the three case studies in selected countries of the Mekong 
Country. Assumptions and parameters used for technical and economic performance 
are described. In the research, an analysis evaluates village scale systems by using 
RES software. Each system was evaluated at its maximum energy demand (kWh). In 
order to compare the technical and economics of different technologies and 
renewable energy resources, an analysis was based on SERT & CORE’s database.   
 
The PVHS under evaluation can serve small village loads, from about 2,500 kWh/y to 
12,500 kWh/y (depend on the solar energy resource and installed capacity). PVHS 
had shown very high PR for every range of villages energy demand (more than 
60%). An average Fsol of the systems is more than 70% and FY is more than 3.0 h/d 
at every energy demand range. The annual power supplied by PV, battery and the 
battery SOC of the system has shown a very interesting point of view for energy 
management systems. Almost all batteries are never full again after its first operation; 
it moves between 0.3 – 0.7 depending on system DOD setting. The battery 
management system may be need for additional study in the future.  
 
Household surveys conducted in the Region indicate that most families consume 500 
– 600 Wh/d, mainly for lighting, radio and small TV set. When a small refrigerator is 
introduced, daily consumption rises to 1.0 -1.5 kWh/d [CORE].    
    
 90
Figure 5-24 shows that PVHS can meet increased energy demand at relative cost 
reduction to the user, improving this system’s competitive standing over DGS, which 
can suffer long down-time due to maintenance needs, part failures and fuel shortfalls. 
COE of the PVHS is moves from 0.50 – 0.30 €/kWh, PVS is 0.70 – 0.50 €/kWh, DGS 
is 0.60 – 0.40 €/kWh and GE is 1.00 – 0.80 €/kWh. 
 
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000
Energy demand (kWh/y)
C
O
E 
(€
/k
W
h)
GEPVHS PVS DGS
 
Figure 5-24: Levelized costs for PVHS, PVS, DGS and GE in selected countries of Mekong Country 
 
The PVHS has shown very attractive results in both technical and economic 
performance for their rural electrification in the Mekong Country, especially in 
countries like Cambodia, Lao PDR Myanmar and Vietnam, which have a low percent 
of rural household electricity access (see Chapter 2).      
 
 
 
 
 
 
 91
6 CONCLUSIONS AND RECOMMENDATIONS 
 
Rural electrification is now and will remain an essential element for rural areas of the 
Mekong Countries. Renewable energy technologies, such as photovoltaic hybrid 
systems can provide an economical option for meeting energy demands of remote 
rural villages in these regions. The most frequent reasons for PV project failure are 
system designs that are not appropriate to the user, improper component selection, 
installation and most importantly lack of quality technical and economic pre-feasibility 
studies.  
 
This research covered four aspects: 
• Implementation of field tests, monitoring and evaluation of the PVHS at Energy 
Park of School of Renewable Energy Technology in order to test the PVSH 
working under the metrological conditions of the Mekong Country (Chapter 3). 
• Develop a software simulation, which studies the technical and economic 
performance of rural electrification options. This software must be easy to use and 
understand for the energy planner on rural electrification projects (Chapter 4)  
• Evaluate the technical and economic performance of the PVHS base on 
renewable energy potential for rural electrification of Mekong Country by using the 
developed software (Chapter 5). 
• To give guidance for the possible use of PVHS application in this region, 
particularly in regard to its technical and economic sustainability (Chapter 5) 
 
The following conclusion may be drawn from these results: 
• The implementation of field test has successfully been done in the context of a 
research project. The PVHS installation based on ISET concept has proven to be 
an efficient operation for power supply systems. The evaluation of the system 
shown the FY is about 3.5 kWh/kWp and the daily average energy produced by 
diesel generator is 0.12 kWh/kW. The daily average PV energy use is 6.9 kWh. 
The data shows the energy used produced by PV is about 79%. The PR of system 
is 66.6% indicates that on an annual base under the prevailing conditions 33.4% of 
the nominal energy is not available for load supply due to losses in reflection, 
higher module temperature, cable and conversion losses, even if the station is 
continuously used.  
 92
• RES is a sizing, simulation and economic analysis tool for both renewable energy 
and conventional energy technology applications. Renewable technology consists 
of PV-Diesel Hybrid System, Stand-alone PV Station, Solar Home System and 
Centralized PV Battery Charging Station. Conventional technology consists of 
Stand-alone Diesel Generator Station and Grid Extension. The technical result 
shows all energy data which are useful when used for comparison with other 
system types. The economics result shows net present value, life cycle costs and 
levelized costs of each system which the user can use to compare with another 
system technology. This software can offer highly accurate results based on the 
actual meteorological database input by the user for each area. This software 
serves as a useful tool for energy planners and system designers when selecting 
the most appropriate rural electrification option and offering the most optimal 
technical and economic benefits for the people living in rural areas. 
• The PVHS under evaluation can serve a small village load, from about 1000 
kWh/y to 15000 kWh/y. PVHS has shown very high PR for every range of villages 
energy demand (more than 60%). An average Fsol of the systems is more than 
70% and FY is more than 3.0 h/d at every energy demand range. The annual 
power supplied by PV, battery and the battery SOC of the system has shown a 
very interesting point of view for energy management systems. Almost all batteries 
are SOC moves between 0.3 – 0.8 depending on the system DOD settings. PVHS 
can meet increased energy demand at relative cost reduction to the user, 
improving this system’s competitive standing over DGS, which can suffer long 
down-time caused by maintenance needs, part failures and fuel shortfalls. COE of 
the PVHS is moving from 0.50 – 0.30 €/kWh, PVS is 0.70 – 0.50 €/kWh, DGS is 
0.60 – 0.40 €/kWh and GE is 1.00 – 0.80 €/kWh. 
 
6.1 Outlook and future work 
 
Most of the current PV projects have been made without technical and economic pre-
feasibility study. Nevertheless, the rate of system failures in even these systems is 
less than that of small diesel generator system for rural electrification. This is an 
indication of the reliability of the PV. The combination of PV and diesel generator so 
call hybrid system presents an attractive option for rural electrification of the Mekong 
Country. But in real situations, there are still many problems the need to be studied in 
the future such as actual system operation and reliability.  System developments are 
 93
not enough for PV rural electrification projects. PVHS promotion should be made 
following the principle of proper design and adequate maintenance is performed; the 
number of satisfied users will be increase. PVHS is not the only choice for rural 
electrification but it is one of the proper choices for the Mekong Country. Other 
renewable energy options such as wind, biomass and hydro power need to be 
studied in the future.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 94
 
 
 
 
 
 
 
 95
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 100
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Minh City, Vietnam, 6-10 February 2001.  
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 101
8 APPENDICES 
 
8.1 Appendix A: The hybrid system prototype drawing 
 
Table 8-1: Components list 
Designation Description Properties/Comments 
A1 Distribution box 35x52 cm 
A2 Battery inverter SMA Sunny Island 3300 
A3 Grid connected inverter SMA Sunny Boy 1700E 
A4 Datalogger SMA Sunny Boy Control 
A5 Datalogger Delphin topmessage 
A6 Circuit breaker distribution box 25x35 cm 
A7 Simulator load Heater 500W x 6, Variable 0-3,000W, Voltage range 
200-240V, max. current 15A  
A8 Generator junction box 
A9 Generator A/Hz meter panel box 20x30 cm 
A10 DC Power Supply, 24V Power 10W reguired for Delphin topmessage 
A11 DC Power Supply, 12V Required for Energy Meter 
B1 Sensor battery temperature for Sunny Island PT100 
B2 Sensor module temperature PT100 
B3 Sensor ambient temperature PT100 
B4 Pyranometer Kipp & Zonen CM11, Sensitivity 5.02 µV/W/m2 
C1 Sunny Boy connector for data transmission cable 
E1 Ventilator fan 
F1 Fuse switch disconnector of PV Array (+) 30A 
F2 Fuse switch disconnector of PV Array (-) 30A 
F3 Fuse switch disconnector of Battery (+) 63A 
F4 Fuse switch disconnector of Battery (-) 63A 
F5 Fuse switch disconnector of AC outlet (L) 16A/400V 
F6 Fuse switch disconnector of AC outlet (N) 16A/400V 
F7 Battery inverter AC outlet circuit breaker 30A 
F8 Grid connected inverter AC outlet circuit breaker 30A 
F9 Diesel Generator AC outlet circuit breaker 30A 
F10 Consumer load circuit breaker 30A 
F11 Simulator load circuit breaker 30A 
F12 Village load circuit breaker 30A 
F13 Water pumping circuit breaker 30A 
G1 Battery Bank 60V, 18 kWh, EXIDE TECHNOLOGIES, CLASSIC 4 
SOLAR 305 
G2 PV Array 2kWp, BP SOLAR 75Wp @ 26 module 
G3 Diesel Generator 5kVA, HONMAR 5GFLE 
K1 Relay for control of diesel generator contactor circuit  
K2 Relay for control of load contactor circuit 
K3 Solid state relay  For adjust simulator load 
L1 LED lamp of Heater1 
L2 LED lamp of Heater2 
L3 LED lamp of Heater3 
L4 LED lamp of Heater4 
L5 LED lamp of Heater5 
L6 LED lamp of Heater6 
M1 Ampare Meter panel of simulator load 
R1 Heater1 500W 
R2 Heater2 500W 
R3 Heater3 500W 
R4 Heater4 500W 
R5 Heater5 500W 
R6 Heater6 500W 
S1 Switch for Heater1 
S2 Switch for Heater2 
S3 Switch for Heater3 
S4 Switch for Heater4 
S5 Switch for Heater5 
S6 Switch for Heater6 
S7 Regulator switch 
T1 Current Transformer Diesel Current max. input current 25A, output current 5A, CARLO 
GAVAZZI 
T2 Timer switch for Heater1 
T3 Timer switch for Heater2 
T4 Timer switch for Heater3 
T5 Timer switch for Heater4 
 
 102
 
Table 8-1: Components list (continue) 
Designation Description Properties/Comments 
T6 Timer switch for Heater5 
T7 Timer switch for Heater6 
P1 Diesel Generator Energy Meter NIEAF MEASURING, SWHM-12; 1-phase kWh-meter, 
20A, 230Vac 
P2 Simulator load Energy Meter NIEAF MEASURING, SWHM-12; 1-phase kWh-meter, 
20A, 230Vac 
P3 Control room Energy Meter NIEAF MEASURING, SWHM-12; 1-phase kWh-meter, 
20A, 230Vac 
P4 Village load Energy Meter NIEAF MEASURING, SWHM-12; 1-phase kWh-meter, 
20A, 230Vac 
P5 Water pumping Energy Meter NIEAF MEASURING, SWHM-12; 1-phase kWh-meter, 
20A, 230Vac 
X3 Modular Terminals  
X4 Modular Terminals  
X5 Modular Terminals  
X6 Modular Terminals  
X7 AC grid connected sockets Power from Hybrid System 
X8 AC grid connected sockets Power from Hybrid System 
X9 Public grid connected sockets Power supply for Delphin datalogger and kWh-meter 
X10 Public grid connected sockets Power supply for Delphin datalogger and kWh-meter 
X11 Modular Terminals  
X12 Modular Terminals  
X13 Modular Terminals  
X14 Modular Terminals  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 103
 
 
 
 
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 106
 
 
 
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 107
 
 
 
 
 
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 108
 
 
 
 
 
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A2
A4
RELAISOUT
PC(COM2)
SUNNYBOY
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POWER
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 110
 
 
 
 
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 111
8.2 Appendix B: The algorithms and user interface of RES 
 
 
 
Figure 8-1: PVHS grid tried algorithm 
 
 
 
Start
Power from PV
(PArray)
PInv = PArray x InvEff
PLine = PInv
Compare
PLine & PLoad
Load Requirement
(PLoad)
PLine < Pload
PLine >= Pload
PLine = PLine - PLoad
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Return
PBattRef = (1-MaxDOD) x BattCap
PLine = PLine - PLoad
PBattMaxDis = ((PBatt-PBattRef)xBattEff)xBattInvEff
Compare
(-PLine) & PBattMaxDis
(-PLine) > PBattMaxDis
(-PLine) <= PBattMaxDis
PBattDis = (-PLine)
BattSOC = PBatt/BattCap
Return
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
Return
DieselHr = DieselHr + 1
Compare
PLine +
(DieselCapxDieselEff)
and 0
case <0
case >= 0
Return
PChgBatt = (PLine x
BattInvEff)xBattEff
PNetPV = PLoad
PNetPV = PLine
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Return
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
Return
PDiesel = DieselCapxDieselEff
PLine = PLine+(DieselCapxDieselEff)
PChgBatt = (PLine x
BattInvEff)xBattEff
PDiesel = DieselCapxDieselEff
PLine = PLine+(DieselCapxDieselEff)
PLack = (-PLine)
PBatt = PBatt - (PBattDis/
(BattEffxBattInvEff)
 112
 
 
 
 
 
Figure 8-2: PVHS grid forming algorithm 
 
 
 
Start
Power from PV
(PArray)
PInv = PArray x InvEff
PLine = PInv
Compare
PLine & PLoad
Load Requirement
(PLoad)
PLine < Pload
PLine >= Pload
PLine = PLine - PLoad
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Return
PBattRef = (1-MaxDOD) x BattCap
PBattMaxDis = ((PBatt-PBattRef)xBattEff)xBattInvEff
Compare
(PLine + PBattMaxDis)
and PLoad
case < PLoad
case >= PLoad
PBattDis = PLoad -PLine
BattSOC = PBatt/BattCap
Return
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
Return
PNetPV = 0
PBattDis = 0
Compare
PLine & PLoad
PLine < PLoad
PLine >= PLoad
Return
PChgBatt = (PLine x
BattInvEff)xBattEff
PNetPV = PLoad
Return
PDiesel = PLine
DumpLoad = PLine - Pload
PDiesel = 0
PLack = PLoad
PNetPV = PLine
PBatt = PBatt - (PBattDis/
(BattInvEffxBattInvEff)
PLine = DieselCapxDieselEff
 113
 
 
 
 
Figure 8-3: PVS algorithm 
 
 
 
Start
Power from PV
(PArray)
PInv = PArray x InvEff
PLine = PInv
Compare
PLine & PLoad
Load Requirement
(PLoad)
PLine < Pload
PLine >= Pload
PChgBatt = (PLine x BattInvEff)xBattEff
PLine = PLine - PLoad
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Return
PBattRef = (1-MaxDOD) x BattCap
PLine = PLine - PLoad
PBattMaxDis = ((PBatt-PBattRef)xBattEff)xBattInvEff
Compare
(-PLine) & PBattMaxDis
(-PLine) <= PBattMaxDis
(-PLine) > PBattMaxDis
PLack = (-PLine)
Return
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
Return
PBattDis = (-PLine)
Return
PNetPV = PLine
PNetPV = PLine
PBatt = PBatt-(PBattDis(BattEffxBattInvEff))
BattSOC = PBatt/BattCap
 114
 
 
 
 
Figure 8-4: SHS algorithm 
 
 
Start
Get Parameter
(PLoad)
Get Parameter
(PLine)
Comparision
PLoad & PBattDis
Pload > PBattDis
Pload <= PBattdis
PBattDis = PLoad
PBatt = PBatt-(PBattDis/(BattEff*ChgEff))
Return
PLack = PLoad
Return
PChgBatt = (PLine x ChgEff)*BattEff
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
BattSOC = PBatt/BattCap
 
 115
 
 
 
 
 
Figure 8-5: BCS algorithm 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Start
Get Parameter
PLoad = (1-(PBatt/BattCap))xBattCap
Get Parameter
(PLine)
Return Return
PChgBatt = (PLine x ChgEff)*BattEff
PBatt = PBatt + PChgBatt
Compare
PBatt & BattCap
PBatt >= BattCap
PBatt < BattCap
BattSOC = PBatt/BattCap
Psurplus = PBatt - BattCap
PBatt = BattCap
BattSOC = 1
PNetPV = PChgBatt
 116
 
 
 
 
 
 
Figure 8-6: DGS (left) and GE (right) algorithm 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Start
Get Parameter
(PLoad)
Get Parameter
(PLine)
Comparision
PLoad & PLine
Pload >= PLine
Pload < PLine
PDieselUse = PLoad
PSurplus = PLine - PLoad
Return
PDieselUse = PLine
PLack = PLoad - PLine
Return
Start
Find Real Interest Rate
Find Total Initial Cost
Return
Find Annual Cost
Find Replacement Cost
Find Life Cycle Cost  (LCC)
Find Salvage Value
Find Net Present Value (NPV)
Find Levelized Cost
 117
 
 
 
 
Figure 8-7:  Main input user interface of PVHS  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
     
Figure 8-8:  Example of Input data of PV panel, inverter and battery inverter  
 
 118
 
 
 
Figure 8-9:  Solar radiation input user interface  
 
 
 
 
Figure 8-10:  Load input user interface  
 
 119
   
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8-11:  System 
parameter result interface  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8-12:  Energy 
consumption result 
interface 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8-13:  Balance of 
energy result interface 
 120
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8-14:  System 
performance result 
interface 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8-15:  Economics 
result interface