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基于改进粒子群算法的节能调度下多目标负荷最优分配 被引量:36

An Improved Particle Swarm Optimization Based Multi-Objective Load Dispatch Under Energy Conservation Dispatching
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摘要 在传统经济负荷分配模型的基础上,结合节能调度的宗旨,建立了系统有功网损最小和机组发电耗煤量最小的多目标负荷分配模型。该模型改进了基于Pareto最优概念的多目标粒子群算法,将其应用于多目标负荷最优分配,能对系统进行整体节能优化。IEEE57节点系统仿真结果表明,该方法在满足系统的安全约束的同时,能降低系统网损和减少机组煤耗,有效节约能源。通过每次优化求得一组Pareto最优解集能够为决策者提供更多的有效参考,具有实际意义。 On the basis of traditional economic load dispatch and combining with the objectives of energy conservation dispatching, a multi-objective load dispatch model that considers minimum active network loss and minimum coal consumption of generating sets is built. The built model can optimize energy conservation of whole system. In this paper the multi-objective particle swam algorithm based on Pareto optimum is improved and applied to multi-objective optimal load dispatch. Simulation results of IEEE 57-bus test power system show that using the proposed method the network loss of power system and coal consumption of generating sets can be reduced, and energy source can be conserved, meanwhile, the security constraints of power system can be satisfied. Through each time of running of the proposed method, a group of Pareto optimal solution can be achieved, so that more effective references can be offered to decision-makers.
出处 《电网技术》 EI CSCD 北大核心 2009年第5期48-53,共6页 Power System Technology
关键词 经济负荷分配 节能调度 粒子群算法 混沌优化 多目标优化 economic load dispatch energy conservation dispatch particle swarm algorithm chaos optimization multi-objective optimization
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