解决电力市场无功优化问题的序优化级联编码遗传算法  

Ordinal-based genetic algorithm with cascaded encoding for reactive power optimization of electricity market

作　　者：赵大溥[1] 何光宇[1] 钟金[2] 倪以信[2] 

机构地区：[1]清华大学电机工程与应用电子技术系电力系统国家重点实验室,北京100084 [2]香港大学电机电子工程系,中国香港

出　　处：《电力自动化设备》2008年第2期1-5,共5页Electric Power Automation Equipment

摘　　要：发电机和并联补偿设备是系统中主要的无功源,负责满足负荷的无功需求并维持系统电压水平。在电力市场环境下,对无功的优化调度要考虑各类无功电源的成本,并以此作为建立无功市场机制的基础。建立了一个在电力市场环境下考虑无功成本的无功优化模型,该模型将电容的投切标志作为0-1变量,即描述为一个非线性混合整数规划问题,采用级联编码的遗传算法解决该非线性混合整数规划问题。引入了序优化的思想,以指导遗传算法的个体选择和进化代数,并对计算结果的可靠性进行定量评估。在IEEE 30母线系统上的仿真结果验证了该方法的有效性。根据5种情况的计算结果,分析了考虑无功成本时系统的运行状况以及相应的经济效益。Generators and capacitors are main reactive power sources for reactive load demands and system voltage stability. The cost of reactive power resource should be considered in dispatch optimization,based on which the reactive power market is built. A reactive power optimization model based on reactive power cost is proposed,which regards the on- off of capacitor as 0-1 variable. The reactive power optimization becomes the nonlinear programming of mixed integers,to which genetic algorithm with cascaded encoding is applied. The ordinal optimization theory is introduced to direct the individual selection and generation times of geneetie algorithm. Its reliability is evaluated quantitatively. Simulation results of IEEE 30- bus system show its effectiveness. The operating conditions and relevant benefits are analyzed based on 5 eases.

关 键 词：遗传算法 序优化 无功优化 机会成本 混合整数优化 

分 类 号：TM73[电气工程—电力系统及自动化]