Aufsatz
A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization
Zusammenfassung
Combining switching state optimization (SSO) and network expansion planning (NEP) in AC systems results in a mixed-integer non-linear optimization problem. Two methodically different solution approaches are mathematical programming and heuristic methods. In this paper, we develop a hybrid optimization method combining both methods to solve the combined optimization of SSO and NEP. The presented hybrid method applies a DC programming model as an initialization strategy to reduce the search space of the heuristic. A greedy heuristic ensures that the obtained solutions are AC feasible. We compare the hybrid method with other heuristic methods and three mathematical programming models on the same set of planning problems. We show optimization results for four realistic sized power system study cases. Evaluation criteria are convergence, solution cost, and run time. Results show that the hybrid method is able to find a higher number of valid AC-solutions in comparisons to the mathematical programming methods. Furthermore, the obtained solutions have lower expansions costs and are obtained in a shorter run-time compared to the remaining methods for the analyzed study cases. As an addition to this paper, the hybrid implementation and the defined benchmark cases are available as open-source software.
Zitierform
In: IEEE Open Access Journal of Power and Energy Volume 7 (2020-07-01) , S. 234-242 ; EISSN: 2687-7910Förderhinweis
Gefördert durch den Publikationsfonds der Universität KasselZitieren
@article{doi:10.17170/kobra-202009091753,
author={Schäfer, Florian and Scheidler, Alexander and Braun, Martin},
title={A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization},
journal={IEEE Open Access Journal of Power and Energy},
year={2020}
}
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2020-09-09T12:05:29Z 2020-09-09T12:05:29Z 2020-07-01 doi:10.17170/kobra-202009091753 http://hdl.handle.net/123456789/11792 Gefördert durch den Publikationsfonds der Universität Kassel eng Namensnennung 4.0 International http://creativecommons.org/licenses/by/4.0/ greedy algorithms heuristic algorithms mathematical programming optimization methods power system planning 004 510 A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization Aufsatz Combining switching state optimization (SSO) and network expansion planning (NEP) in AC systems results in a mixed-integer non-linear optimization problem. Two methodically different solution approaches are mathematical programming and heuristic methods. In this paper, we develop a hybrid optimization method combining both methods to solve the combined optimization of SSO and NEP. The presented hybrid method applies a DC programming model as an initialization strategy to reduce the search space of the heuristic. A greedy heuristic ensures that the obtained solutions are AC feasible. We compare the hybrid method with other heuristic methods and three mathematical programming models on the same set of planning problems. We show optimization results for four realistic sized power system study cases. Evaluation criteria are convergence, solution cost, and run time. Results show that the hybrid method is able to find a higher number of valid AC-solutions in comparisons to the mathematical programming methods. Furthermore, the obtained solutions have lower expansions costs and are obtained in a shorter run-time compared to the remaining methods for the analyzed study cases. As an addition to this paper, the hybrid implementation and the defined benchmark cases are available as open-source software. open access Schäfer, Florian Scheidler, Alexander Braun, Martin doi:10.1109/OAJPE.2020.3006344 Greedy-Algorithmus Heuristik Programmierung Optimierung publishedVersion EISSN: 2687-7910 IEEE Open Access Journal of Power and Energy 234-242 Volume 7 false
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