A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow

Abstract Optimal Reactive Power Flow (ORPF) is a branch problem in the gradual development of the optimal power flow problem. Differential Evolution (DE) has been proved to be a promising evolutionary algorithm for solving the ORPF problem, but it requires a relatively large population size to avoid premature convergence, which will increase the algorithm convergence time. On the other hand, Artificial Bee Colony (ABC) algorithm has been proved to have good global search ability. Integrating the respective advantages of DE and ABC, a hybrid ABC assisted DE algorithm, denoted as DE–ABC, is proposed in this study to overcome DE’s disadvantage of requiring large population size and strengthen the global search ability. At the last, the effectiveness of DE–ABC is verified by the serial simulations on the IEEE 14-bus, 30-bus and 57-bus system test cases. The simulation results show, in the case of achieving the same effect, the required population size of DE–ABC hybrid algorithm is greatly less than that of DE algorithm, the algorithm convergence time is less too and the algorithm is robust.

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