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Neural Computing and Applications

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22.06.2019 | Original Article

Solution of the optimal power flow problem considering security constraints using an improved chaotic electromagnetic field optimization algorithm

verfasst von: Houssem Bouchekara

Erschienen in: Neural Computing and Applications | Ausgabe 7/2020

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Abstract

The main objective of this paper is to solve different configurations of the optimal power flow (OPF) problem efficiently using an improved version of the newly proposed electromagnetic field optimization (EFO) algorithm. The developed and improved new version of EFO is based on chaotic maps and on a new mechanism. This improved version is called improved chaotic electromagnetic field optimization (ICEFO) algorithm. The performances of the ICEFO algorithm are evaluated on a large set of cases using: tow formulations, three objective functions (cost minimization, cost minimization and voltage profile improvement and cost minimization and voltage stability enhancement) and three test systems (the IEEE 30-bus, the IEEE 57-bus and the IEEE 118-bus test systems). The obtained results of the developed algorithm are compared with other well-known algorithms. These results demonstrate that the developed algorithm is able to solve efficiently different configurations of the OPF problem and for different test systems.

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Titel: Solution of the optimal power flow problem considering security constraints using an improved chaotic electromagnetic field optimization algorithm
verfasst von: Houssem Bouchekara
Publikationsdatum: 22.06.2019
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-019-04298-3

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