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基于改进粒子群算法的电力系统有功调度
引用本文:秦明明,王坚,姜雷.基于改进粒子群算法的电力系统有功调度[J].电力学报,2009,24(6):471-473,477.
作者姓名:秦明明  王坚  姜雷
作者单位:1. 上海东华大学,信息学院,上海,201620
2. 三菱电机上海机电有限公司,上海,201108
摘    要:针对电力系统有功优化调度,提出了一种改进的粒子群算法,该算法考虑了火电厂的煤耗量,污染物排放量,以及线路损耗等,通过分别求解各个单目标优化问题和定义各单项目标的隶属度函数,把多目标优化问题转化为单目标优化问题,从整体上降低电力系统的发电成本。该算法以标准粒子群算法为基础,对其参数进行了改进,并对其搜索速度加以限制。将其应用于电力系统的3机组模型,算例仿真结果表明该算法节省了收敛时间,具有收敛速度快,计算精度高的优点。

关 键 词:电力系统  有功调度  粒子群算法

Electric Power System Active Dispatch Based on Improved Particle Swarm Optimization
QIN Ming-ming,WANG Jian,JIANG Lei.Electric Power System Active Dispatch Based on Improved Particle Swarm Optimization[J].Journal of Electric Power,2009,24(6):471-473,477.
Authors:QIN Ming-ming  WANG Jian  JIANG Lei
Abstract:Active for optimal scheduling of power system,this paper presents an improved particle swarm algorithm,which takes into account the volume of coal consumption of thermal power plants,pollutant emissions,as well as Lines loss.The multi-objective optimal problem can be transformed into single-objective optimal problem by means of respectively solving the various single-objective optimal problems and the definition of the objective of the individual membership function.The cost of power generation is minimized on the whole.This algorithm is based on the standard particle swarm optimization,has improved its parameter and limited the speed of its search.Apply it to 3 unit models of the power system,simulation results show that the algorithm has saved the time of searching,has fast convergence and the advantages of high accuracy.
Keywords:power systems  active scheduling  particle swarm optimization
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