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A novel evaluation framework for energy losses in low voltage distribution grids

Decentralization of energy generation in power distribution systems is recognized as an important development strategy to incorporate more small-scale renewable sources, reduce greenhouse gas emissions and increase energy efficiency. Beside integrating more decentralized generators into existing systems, an efficient system operation is equally important to achieve an overall sustainable energy system. In order to keep track of upcoming changes regarding system efficiency, an accurate determination of energy losses in distribution systems is a fundamental step. Therefore, a novel evaluation framework for energy losses in the low voltage grids is developed in this thesis. First, a loss evaluation approach based on a comprehensive assessment of grid features and an advanced reference grid modeling scheme is proposed. Second, a new analytical indicator is introduced for fast estimation of the grid losses under the impact of the installed distributed generators. For distribution system operators, this new evaluation framework demonstrates a practical and technically validated solution, which can be used as an alternative method to the existing approaches regarding the loss evaluation. Applying this comprehensive evaluation framework for energy losses at a large scale can support grid operators to understand the origin of losses and further development trends. The technical progress of energy losses evaluation can greatly contribute to improve energy efficiency and sustainability of current distribution systems.

Imprint
@book{doi:10.17170/kobra-202008131566,
  author    ={Ma, Chenije},
  title    ={A novel evaluation framework for energy losses in low voltage distribution grids},
  keywords ={600 and Erneuerbare Energien and Niederspannungsnetz and Energieeffizienz and Energieverlust and Dezentrale Elektrizitätserzeugung and Maschinelles Lernen},
  copyright  ={http://creativecommons.org/licenses/by-sa/4.0/},
  language ={en},
  year   ={2020}
}