摘要
考虑了配电网扩展规划条件下新增负荷节点的情况,根据新增负荷总量确定待建分布式电源的总容量,在分布式电源个数、位置和单个电源容量均不确定的情况下,以网络建设成本与运行费用为目标函数,建立了包含DG的配电网规划的多智能体遗传模型。应用多智能体遗传算法对分布式电源的位置、容量及配电网网架进行了整体优化。通过设计多智能体的竞争行为和自学习行为增加目标函数值寻求最优解,实现了全局收敛,提高了收敛速度。
The paper discusses adding new load nodes in distribution system expansion planning.The total installed capapcity of distributed generation expansion is determined according to the amount of new loads.Under the condition that the number of DG units,locations,and the capacity of DG units are unkonwn,a multi-agent genetic model for distribution planning with DGs is proposed,with an objective function of minimizing the network constuction and operation costs.The location,capacity and the topology of the distribution system is golablly optimized by multi-agent genetic algorithm.Through the proper designing of the competition and self-learning behavior for the adjustment of the value of the objective function,fast global convergence is achieved.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2011年第1期87-91,117,共6页
Power System Protection and Control
关键词
配电网规划
分布式发电
多智能体遗传算法
不可行解修复
distribution network planning
distributed generation
multi-agent genetic algorithm
unfeasible solution restoration
