摘要
电力系统经济负荷分配,是指在满足电力系统或发电机组运行约束条件的基础上,在各台机组间合理地分配负荷以达到最小化发电成本的目的,是经济调度中非常重要的问题。粒子群算法是一种源于对鸟群捕食的行为研究的进化计算技术,具有全局优化能力强、收敛性好和编程实现简单等优点。将粒子群算法应用于电力系统经济负荷分配问题的研究中,通过对实际算例进行仿真测试,证实该算法可有效解决经济负荷分配问题,性能对比显示,该算法求得的解优于传统优化算法所求得的解。
Economic load dispatch problem of power system is a very important subject,which achieves a reasonable load dispatch minimizing the cost of electricity on the basis of operation constraints.Particle swarm optimization algorithm is an evolutionary computing technology originating from behavior of bird predation.It possesses global optimization capability,good convergence and simple programming.The particle swarm optimization algorithm is used in the economic load dispatch problem of power system in this paper.Actual simulation is tested and proved the algorithm can solve the economic load dispatch problem efficiently.The comparison shows the solution given by the particle swarm optimization algorithm is better than traditional optimization algorithm.
出处
《山东电力技术》
2010年第6期31-33,共3页
Shandong Electric Power
关键词
电力系统
经济负荷分配
粒子群算法
power system
economic load dispatch
particle swarm optimization algorithm
