Solving multiobjective optimal reactive power dispatch using improved multiobjective particle swarm optimization

In this paper, a novel improved multiobjective particle swarm optimization (IMOPSO) is proposed for solving the optimal reactive power dispatch (ORPD) problem with multiple and competing objectives. In order to improve the global search capability and the nondominated solutions diversity, time variant parameters, mutation operator, and dynamic crowding distance are incorporated into the MOPSO algorithm. In addition, multiple powerful strategies, such as mixed-variable handling approach, constraint handling technique and stopping criteria, are employed. The propose IMOPSO is validated on the standard IEEE 30-bus and IEEE 118-bus systems, and compared with MOPSO and nondominated sorting genetic algorithm( NSGA-II) using performance metrics with respect to convergence, diversity, and computational time. The numerical results demonstrate the superiority of the proposed IMOPSO in solving the ORPD problem while strictly satisfying all the constraints.

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