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文章摘要
基于改进粒子群优化算法的负荷分配方法研究
Research on load distribution method based on improved particle swarm optimization algorithm
Received:January 14, 2020  Revised:January 14, 2020
DOI:DOI: 10.19753/j.issn1001-1390.2022.10.017
中文关键词: 经济环保负荷分配  粒子群优化算法  精英交叉算子  拥挤距离排序
英文关键词: economic and environmental load distribution, particle swarm optimization algorithm, elite crossover operator, congestion distance ranking
基金项目:国家自然科学基金项目( 项目编号61672266)
Author NameAffiliationE-mail
Wei Jiazhu Jiangnan University,Institute of Electrical Automation 1831147129@qq.com 
Pan Ting-long* Jiangnan University tlpan@jiangnan.edu.cn 
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中文摘要:
      针对多目标粒子群优化算法求解负荷优化分配问题时所出现的最优解分布不均、局部最优等问题,引入了精英交叉算子并基于拥挤度对非劣解集进行排序,给出了精确计及网损时的机组出力等式不等式约束处理方法。在忽略和计及网损两种情况下针对3机组系统进行负荷优化分配,仿真结果表明改进后的粒子群优化算法寻优能力得到提升。同样利用模糊隶属度函数筛选Pareto解集,所提方法得到的结果明显优于常规粒子群优化算法,在降低发电成本及污染物排放的同时使得求解结果严格满足约束条件。
英文摘要:
      Aiming at the problem of uneven distribution of the optimal solution and local optimality when the multi-objective particle swarm optimization algorithm is used to solve the problem of optimal load distribution, the elite crossover operator is introduced and the non-inferior solution sets are ranked based on the congestion. This paper presents a method to deal with the equality and inequality constraints of the unit output when the network loss is taken into account accurately. Load optimization distribution is performed for the three-unit system with or without network loss. Simulation results show that the improved particle swarm optimization algorithm has improved the optimization ability. When the fuzzy membership function is used to screen Pareto solution set, the result of the method proposed in this paper is obviously better than that of the conventional particle swarm optimization algorithm, which can reduce the cost of power generation and pollutant emission while making the solution strictly meet the constraints.
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