Abstract：This paper proposes a new approach combining of particle swarm optimization (PSO) and heuristic-adjusted strategies to solve unit commitment (UC) problem in power system. The UC problem is decomposed into two embedded optimization sub-problems: one the unit on/off status schedule problem with integer variables that could be solved by the discrete binary particle swarm optimization method and the other load economic dispatch problem with continuous variables that could be solved by the equal Lambda-iteration method. At the same time, shutdown-adjusted and replacement-adjusted strategies are performed on the optimal results to raise solution quality, which could be effectively enhanced the algorithm’s global optimization performance and computational efficiency. The feasibility and effectiveness of the proposed method are demonstrated for five test systems with the number of generating units in the range of 10 to 100, and the computational results are compared with those previously reported in literature. Simulation results show that the proposed method has advantages for solving UC problem with high precision and quickly convergence speed.
袁晓辉, 苏安俊, 聂浩, 曹波, 杨波. 面向启发式调整策略和粒子群优化的机组组合问题[J]. 电工技术学报, 2009, 24(12): 137-141.
Yuan Xiaohui, Su Anjun, Nie Hao, Cao Bo, Yang Bo. Unit Commitment Problem Based on PSO With Heuristic-Adjusted Strategies. Transactions of China Electrotechnical Society, 2009, 24(12): 137-141.
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