The Frontiers of Society, Science and Technology, 2020, 2(13); doi: 10.25236/FSST.2020.021315.
Gu Zheng, Yang Bo, Liu Songnan
State Grid Liaoning Electric Power CO, LTD. Power Electric Research Institute, Shenyang, Liaoning110015, China
In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the problem. The proposed method, denoted as RPQPSO, combines the QPSO algorithm with random perturbation operation to enhance the global search ability of the algorithm. The perturbation strategy adopts two methods to perturb each particle in the group according to the random probability at the late stage of evolution, so that the algorithm avoids falling into the local optimum. The simulation results show that the proposed RPQPSO method is able to obtain higher quality solutions in the ED problem than any other tested optimization algorithm.
Economic dispatch; constrained optimization; random perturbation; evolutionary computation; particle swarm optimization
Gu Zheng, Yang Bo, Liu Songnan. Enhanced quantum-behaved particle swarm optimization algorithm for power system dispatch problem. The Frontiers of Society, Science and Technology (2020) Vol. 2 Issue 13: 111-117. https://doi.org/10.25236/FSST.2020.021315.
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