基于混合微分演化算法的配电网架结构智能规划  

An Intelligent Distribution Network Planning Method Based on Geographical Differential Evolution

作　　者：刘军[1] 刘自发[1] 黄伟[1] 于晗[1] 张建华[1] 

机构地区：[1]华北电力大学电力系统保护与动态安全监控教育部重点实验室,北京市102206

出　　处：《电力系统自动化》2007年第2期32-35,共4页Automation of Electric Power Systems

摘　　要：应用地理信息系统(GIS)和改进的微分演化(DE)算法组成混合微分演化(GDE)算法来进行配电网架结构的智能规划。该算法首先利用配电网络的地理特征,分阶段过滤明显不适合的线路,得到初步规划网络,随后利用DE算法收敛快速、鲁棒性强的特点,将其应用到优化计算中。为避免早熟,对传统DE算法进行了改进,利用解群转移策略在给定的条件下对解群进行分散处理,以跳出局部最优点,得到全局最优解。并给出了某省会城市的城区高压配电网规划算例。Distribution network planning is a multi-goal multi-phase and multi-restriction problem that involves the geographical condition of power line route, construction and maintenance expenses, power line losses, power flow and security constraint. A model is proposed to minimize the work of planner while simplifying the network planning procedure. The geographical feature is carefully considered to minimize the optimal search scope and improve the efficiency. An improved differential evolution （DE） is used also in optimal calculation. The DE is far more efficient and robust compared to PSO and GA. The DE is improved to prevent the results from becoming locally optimized by adopting the probability distribution feature and regenerating a diverse population of individuals. The application of the method in a provincial capital power network shows that the optimal speed and robustness can be improved by adopting the improved DE and geographical feature pretreatment.

关 键 词：网架规划 地理信息系统 智能算法 微分演化算法 

分 类 号：TM715[电气工程—电力系统及自动化]