Solving Optimal Power Flow Using Cuckoo Search Algorithm with Feedback Control and Local Search Mechanism

摘要

Cuckoo search (CS) algorithm is a novel heuristic algorithm, which can effectively solve the optimization problem by simulating the brood parasitism of some cuckoo species and combining with Levy flight mechanism. However, it has also been shown to have certain weaknesses, especially falling into local optimums. Therefore, a novel CS algorithm with feedback control and local search mechanism (FLCS) is proposed in this paper. In the FLCS, feedback control is introduced to enhance the efficiency of search process, and local search mechanism is guided by the global optimal solution for improving the poor local search ability of CS method. To verify the performance of our approach, 21 test functions of different types are first employed. Then, the FLCS has been performed on the IEEE 30-bus power flow test case for optimal power flow (OPF) problem with valve point effect. The results indicate that the proposed FLCS method clearly has better performance than CS in the solution accuracy and convergence speed. In addition, the comparison results show that FLCS performs better than other evolutionary methods from literature for different functions.