期刊
NEURAL COMPUTING & APPLICATIONS
卷 32, 期 13, 页码 9129-9164出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-019-04425-0
关键词
Stochastic fractal search; Diffusion process; Update process; Optimal power flow; Objective function; Operating limitations
This paper presents the application of an improved stochastic fractal search algorithm (ISFSA) for optimizing five single objectives of optimal power flow (OPF) problem and satisfying all constraints consisting of operating limits of electric components, power balance and load voltage magnitude limits. The proposed ISFSA is formed by implementing three improvements on the conventional stochastic fractal search algorithm (SFSA). The first improvement cancels one ineffective formula but keeps another one in diffusion process. The second improvement selects some worst solutions in the first update and some best solutions in the second update for producing new solutions. In the third improvement, a proposed technique is applied for carrying out the update processes. Comparisons of obtained results from three standard IEEE power systems indicate that the proposed method is superior to SFSA in terms of optimal solution quality, execution speed as well as success rate. The performance comparisons with other existing methods available in previous studies also lead to the conclusions that the proposed method can reach lower generation fuel cost, smaller total power losses, less amount of emission, better voltage profile and faster execution process. As a result, it can be recommended that the proposed ISFSA should be used for OPF problem in high-voltage power system field.
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