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This paper presents an e cient and reliable tabu search (TS)-based approach to solve the optimal power ow (OPF) problem. The proposed approach employs TS algorithm for optimal settings of the control variables of the OPF problem. Incorporation of TS as a derivative-free optimization technique in solving OPF problem signi cantly reduces the computational burden. One of the main advantages of TS algorithm is its robustness to its own parameter settings as well as the initial solution. In addition, TS is characterized by its ability to avoid entrapment in local optimal solution and prevent cycling by using exible memory of search history. The proposed approach has been examined on the standard IEEE 30-bus test system with diOE erent objectives and generator cost curves. The results are promising and show the eOE ectiveness and robustness of the proposed approach.

His research interests include power system control and operation, adaptive and robust control of power systems, and applications of AI techniques in power systems and FACTS.

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