自适应免疫粒子群算法在动态无功优化中应用  

Application of adaptive immune PSO in dynamic reactive power optimization

作　　者：沈茂亚[1] 丁晓群[1] 王宽[1] 侯学勇[1] 徐进东[2] 

机构地区：[1]河海大学电气工程学院,江苏南京210098 [2]泰州供电公司,江苏泰州225300

出　　处：《电力自动化设备》2007年第1期31-35,共5页Electric Power Automation Equipment

摘　　要：根据电力系统实际运行中负荷不断变化的情况,提出了动态无功优化问题的完整数学描述和计算方法。从负荷曲线的特点出发,结合设备动作次数约束,提出利用遗传算法进行智能化负荷分段的方法。利用引入免疫系统的免疫信息处理机制和自动调整动量系数的自适应因子的粒子群算法,从整体上获得系统的最优控制方式。IEEE 30节点系统算例分析表明,该方法有效减少了补偿设备和变压器分接头的动作次数,其中节点12电容器组的投切次数由6次降为2次,且系统在一天内的有功损耗由1.2413p.u.降为1.1554p.u.。With the consideration of the varying load of power system,a complete mathematical representation of dynamic reactive power optimization and its calculation method are presented. According to load characteristics and combined with constraints of device action times, an intellectualized load dividing method using genetic algorithm is proposed. The optimal control mode on the whole is achieved by applying the immune system with immune information transacting mechanism and PSO （Particle Swarm Optimization） with adaptive factor for automatic adjust of momentum coefficient. The simulation on IEEE 30-bus system shows that,the proposed method reduces action times of compensatory devices and transformer taps,in which the switching time of capacitors at bus 12 is reduced from six to two,and the daily active power loss of the system is reduced from 1.241 3 p.u. to 1.1554 p.u..

关 键 词：电力系统 动态无功优化 负荷分段 粒子群算法 

分 类 号：TM761.1[电气工程—电力系统及自动化]