引用本文:陈云超,李兴源,苗 淼,等.基于多精英协同进化单亲遗传算法的光伏电站功率汇集系统多目标分层优化[J].电力系统保护与控制,2016,44(12):29-35.
CHEN Yunchao,LI Xingyuan,MIAO Miao,et al.Multi-objective and hierarchical optimization of power collection system for photovoltaic power plants based on the multi-elite co-evolutionary partheno-genetic algorithm[J].Power System Protection and Control,2016,44(12):29-35
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基于多精英协同进化单亲遗传算法的光伏电站功率汇集系统多目标分层优化
陈云超1,李兴源1,苗 淼1,张祥成2,温生毅3,成 静3,王 曦1
(1.四川大学电气信息学院，四川 成都 610065;2.青海省光伏发电并网技术重点实验室，青海 西宁 810008;
3..国网青海省电力公司经济技术研究院，青海 西宁 810008)
摘要:
针对大型光伏电站功率汇集外送拓扑设计问题，提出一种基于多精英协同进化单亲遗传算法(MCPGA)的多目标分层优化设计方法。首先深入阐述大型光伏电站功率汇集系统的构成，建立详细的数学优化模型。其次采用所提出的多精英协同进化单亲遗传算法进行拓扑结构优化设计，运用蒙特卡罗法进行可靠性分析。将经济性和可靠性指标作为汇集系统拓扑结构优化设计的评定指标。最后通过一算例仿真验证，所提方法是有效和实用的，算法收敛速度较快，从而为大型光伏电站汇集拓扑规划提供了有效的优化设计方法。
关键词:  光伏电站  功率汇集  单亲遗传算法  经济性优化  可靠性分析
DOI：10.7667/PSPC151440
分类号:
基金项目:国家电网公司科技项目(522830140003)
Multi-objective and hierarchical optimization of power collection system for photovoltaic power plants based on the multi-elite co-evolutionary partheno-genetic algorithm
CHEN Yunchao1,LI Xingyuan1,MIAO Miao1,ZHANG Xiangcheng2,WEN Shengyi3,CHENG Jing3,WANG Xi1
(1. School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, China; ;2. State Key Laboratory
of Photovoltaic Grid Connected Technology, State Grid Qinghai Electric Power Company, Xining 810008, China;
;3. Economic Research Institute, State Grid Qinghai Electric Power Company, Xining 810008, China)
Abstract:
In view of the topological designed problem of power collection system for photovoltaic power plants, the multi-objective and hierarchical optimization based on the multi-elite co-evolutionary partheno-genetic algorithm (MCPGA) is proposed. Firstly, the composition of power collection system is expounded, the corresponding mathematical optimization model is established. Secondly, the MCPGA is used to solve the model, the reliability of collection system is evaluated by Monte Carlo. The economy goal and reliability index are used to evaluate the design of power collection system. At last, simulation results show that this method is effective and practical, convergence of the MCPGA is fast, which can give a coordinate plan of power collection system for photovoltaic power plants.
Key words:  photovoltaic power plants  power collection system  single parent algorithm  economic optimization  reliability analysis
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