遗传蚁群融合算法及在不确定性无功优化中的应用研究  

The fusion algorithm of genetic and ant colony and its application in uncertain reactive power optimization

作　　者：周申培[1,2] 严新平[2] 

机构地区：[1]武汉理工大学自动化学院,湖北武汉430070 [2]武汉理工大学水路公路交通安全控制与装备教育部研究中心,湖北武汉430063

出　　处：《电力系统保护与控制》2010年第24期120-123,共4页Power System Protection and Control

基　　金：国家基础研究计划973计划(2005CB724205)

摘　　要：在双层规划的理论基础上,针对电网无功优化中的负荷不确定性问题,建立了以网损最小为上层优化目标、以满足电压约束条件为下层优化目标的电力系统无功优化模型。并将遗传算法和蚁群算法结合起来用于求解,采用遗传算法生成信息素的初始分布,利用蚁群算法求精确解。以IEEE30节点系统作为试验系统,验证了无功优化模型及算法的正确性和有效性。Based on bi-level programming theory ,a reactive power optimization model for power system is proposed to solve the problem of uncertain load .On the upper level,the sum of transmission loss is minimized, while the lower level optimization ensures that voltage constraints are satisfied .The fusion algorithm of genetic and ant colony algorithm adopts genetic algorithm to give pheromone to distribute, and then it makes use of ant colony algorithm to give the precision of the solution.Furthermore, the numerical example of IEEE 30-bus system is employed to validate the correctness and effectiveness of the model and algorithm.

关 键 词：无功优化 双层规划 融合算法 遗传算法 蚁群算法 

分 类 号：TM714[电气工程—电力系统及自动化]