【摘要】 为解决电力系统环境经济调度这一复杂多目标约束优化问题,提出一种有效多种群合作协同优化算法,采用多个种群对搜索空间进行搜索,运用新型的速度位移更新方式以及种群周期内拓扑结构重组策略.结果表明,该算法能对解空间进行更加全面、充分的探索,可快速找到一组分布具有尽可能好的逼近性、宽广性和均匀性的最优解集合.将该算法应用到某电力系统的环境经济调度中,其仿真计算结果与其他求解方法结果的对比分析表明,该算法可以有效兼顾全局收敛性和Pareto非劣调度方案的多样性,具有较高的效率以及鲁棒性.更多还原

【Abstract】 An effective co-evolutionary multi-swarm particle swarm optimization(ECMPSO)is proposed for environmental-economic dispatch(EED), which is a complicated multi-objective constrained problem.The strategies such as multi-swarm,new particle swarm optimization(PSO)update as well as restructuring topology structure strategy with dynamic population in period are introduced in ECMPSO,so the algorithm has strong global search ability and good robust performance.Some typical multiobjective optimization functions are tested to verify the algorithm,the results show that the proposed algorithm has superior performance of faster convergence speed and strong ability to jump out of local optimum.The proposed algorithm is applied to solve the EED problem of a power system,experimental results demonstrate the successful application of ECMPSO,compared with other methods,ECMPSOoutperforms in globe convergence and the diversity of the Pareto set with higher effectiveness and robustness.更多还原