Optimization method for short circuit current reduction in extensive meshed LV network
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Date
2023-05-10
Authors
Topolánek, David
Krčál, Vít
Foltýn, Ladislav
Praks, Pavel
Vysocký, Jan
Praksová, Renata
Prettico, Giuseppe
Fulli, Gianluca
0000-0001-9754-6867Advisor
Referee
Mark
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Publisher
Elsevier
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Abstract
This paper focuses on the analysis of suitable optimization methods applied to large meshed low-voltage networks. The introduced methods aim to minimize the SC-current contribution by simultaneously fulfilling well-defined operational constraints. The high number of binary variables (134) used in the worst case to determine the possible network configurations generates 1040 possible solutions. For this reason, the paper focuses only on methods capable of reducing the necessary steady-state calculations to a tractable size. Depending on the case under study, the deterministic method turns to be faster than the other ones at the price of reaching only a local minimum. In contrast, if a longer computation time is tolerated, then evolutionary algorithms succeed in finding the global optimum.
This paper focuses on the analysis of suitable optimization methods applied to large meshed low-voltage networks. The introduced methods aim to minimize the SC-current contribution by simultaneously fulfilling well-defined operational constraints. The high number of binary variables (134) used in the worst case to determine the possible network configurations generates 1040 possible solutions. For this reason, the paper focuses only on methods capable of reducing the necessary steady-state calculations to a tractable size. Depending on the case under study, the deterministic method turns to be faster than the other ones at the price of reaching only a local minimum. In contrast, if a longer computation time is tolerated, then evolutionary algorithms succeed in finding the global optimum.
This paper focuses on the analysis of suitable optimization methods applied to large meshed low-voltage networks. The introduced methods aim to minimize the SC-current contribution by simultaneously fulfilling well-defined operational constraints. The high number of binary variables (134) used in the worst case to determine the possible network configurations generates 1040 possible solutions. For this reason, the paper focuses only on methods capable of reducing the necessary steady-state calculations to a tractable size. Depending on the case under study, the deterministic method turns to be faster than the other ones at the price of reaching only a local minimum. In contrast, if a longer computation time is tolerated, then evolutionary algorithms succeed in finding the global optimum.
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Citation
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS. 2023, vol. 152, issue 1, p. 1-10.
https://www.sciencedirect.com/science/article/pii/S0142061523002600?via%3Dihub
https://www.sciencedirect.com/science/article/pii/S0142061523002600?via%3Dihub
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Peer-reviewed
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en
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://creativecommons.org/licenses/by-nc-nd/4.0/