摘要
分布式能源接入配电网是智能电网建设的重要内容之一,合理地对分布式电源进行选址和定容是解决分布式电源合理规划的关键。本文提出一种解决配电网分布式电源规划的协同智能体进化算法,利用智能体的竞争和自学习行为,利用罚函数法将分布式能源规划问题转化为无约束求极值问题,有效提高算法的性能,在IEEE 33节点和69节点配电网测试系统仿真实验中取得了满意的结果。
The connection of distributed generation to distribution network is one of the important contents of smart grid construction. The distributed generation siting and sizing in distribution system is the key to reasonable planning.This paper proposes a multi-agent co-evolutionary algorithm（MACEA） for distributed generation（DG） planning in a distribution system.MACEA is utilized to solve the proposed distributed generation planning model.And combined with penalty function,the DG planning problem is transferred into a problem to solve extreme-value without constraints.Simulation results of the proposed algorithm by IEEE 33-bus and 69-bus distribution test systems show that the MACEA can minimize line losses of distribution systems effectively.
出处
《陕西电力》
2010年第12期6-10,共5页
Shanxi Electric Power
基金
自然科学基金61001206
中国智能交通科技集团项目103-0335资助项目
关键词
分布式电源规划
协同多智能体进化
有功网损
distributed generation planning
multi-agent co-evolutionary
active power loss
