Abstract
The major functions involved in power system security analysis are security assessment and security enhancement. The contingency analysis plays a vital role in the security assessment which has been carried out based on the performance index. Security enhancement incorporates security constrained optimal power flow (SCOPF) which ensures that system is operating at normal state by taking preventive and control actions. An improved artificial physics optimization (APO) evolutionary algorithm is presented in this paper for solving SCOPF problem. The trial and error approach is used for selection of gravitational constant (G) in standard APO method. In order to circumvent this problem, a fuzzy approach is used to tune the gravitational constant (G). Simulations are done on IEEE 30-bus system, Indian 75-bus system, and IEEE 118-bus test system. To evaluate the robustness, results obtained using the proposed method are compared with results obtained using standard conventional algorithms, namely APO, Bat algorithm, and genetic algorithm. The obtained results indicate that the proposed fuzzy adaptive artificial physics optimization (FAAPO) method is efficient as well as robust for solving SCOPF problem to get near global optimization solution compared to standard APO algorithm and other heuristic methods reported in the literature.
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Schedule a callMore From: Journal of The Institution of Engineers (India): Series B
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