摘要
针对当前含有大量具有间歇性的分布式可再生电源接入的主动配电网,通过引入多智能体系统(MAS)思想,提出改进的拓扑重构方法和粒子群算法优化(PSO)协同寻优的多目标动态拓扑重构的算法设计.相对于已有的配电网拓扑重构解决方案,通过采用基于事件驱动的重构触发机制,降低拓扑重构频率以降低重构对配电网运行的负面影响,在重构算法设计中兼顾了经济性和安全性指标优化的同时,降低了优化算法的复杂度.结合IEEE-33节点和美国PG&E 69节点2个典型算例,对该方法进行仿真实验验证.实验结果表明,采用该方法能够有效地计及随机性以及不确定因素对配电网重构的影响,具有良好的计算效率和算法稳定性.
A multi-agent system（MAS）based optimization framework was presented and the particle swarm optimization（PSO）algorithm was incorporated to identify the optimal topology reconfiguration scheme in a cooperative manner for active distribution network with distributed generation（DG）.Compared with the existing solutions,the approach can significantly reduce the negative impact due to frequent reconfigurations based on event-driven mechanism,while promotes the power supply security and economical benefits.The proposed algorithm solution was evaluated by using the IEEE 33-bus and PG＆E69-bus networks as the test networks.The numerical results demonstrate the effectiveness of the suggested approach in finding the optimal topology reconfiguration solution with acceptable computational complexity and communication overhead.
出处
《浙江大学学报（工学版）》
EI
CAS
CSCD
北大核心
2015年第10期1982-1989,共8页
Journal of Zhejiang University：Engineering Science
基金
浙江省自然科学基金重点资助项目(Z15E070001)
浙江省公益性技术应用研究计划资助项目(2013C31005)
关键词
配电网
分布式电源
多智能体
粒子群
最短路算法
层次分析法(AHP)
distribution network
distributed generation
multi-agent
particle swarm
shortest path algorithm
analytic hierarchy process（AHP）
