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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 11/2017

16.03.2016 | Original Article

Symbiotic organisms search algorithm for optimal power flow problem based on valve-point effect and prohibited zones

verfasst von: Serhat Duman

Erschienen in: Neural Computing and Applications | Ausgabe 11/2017

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Abstract

In this study, symbiotic organisms search (SOS) stochastic method is proposed to solve the optimal power flow (OPF) problem with valve-point effect and prohibited zones, which is one of the most important problems of the modern power system. The SOS approach is defined as the symbiotic relationships observed between two organisms in the ecosystem, which do not need the control parameters unlike other meta-heuristic algorithms in the literature. The effectiveness of the proposed SOS method is tested on modified IEEE 30-bus test system. The OPF problem is considered with four different test cases, such as (1) without valve-point effect and prohibited zones, (2) with valve-point effect, (3) with prohibited zones and (4) with valve-point effect and prohibited zones. The obtained results from the SOS algorithm are compared with the other optimization techniques in the literature. The obtained comparison results indicate that proposed approach is effective to reach optimal solution for the OPF problem.
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Metadaten
Titel
Symbiotic organisms search algorithm for optimal power flow problem based on valve-point effect and prohibited zones
verfasst von
Serhat Duman
Publikationsdatum
16.03.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 11/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2265-0

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