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Solving the Economic Dispatch Problem with Q-Learning Quantum-Behaved Particle Swarm Optimization Method

In this paper, a Q learning quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method enhance the global search ability of the algorithm. The feasibility of the QlQPSO method is demonstrated by three different power systems, compared with the GIQPSO, the MeQPSO, and the SlQPSO in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QlQPSO method is able to obtain higher quality solutions stably and efficiently in the ED problem than other tested optimization algorithm.