摘要
应用改进的粒子群算法对单元机组多目标协调优化控制问题进行了研究。为了提高粒子群算法PSO(Particle Swarm Optimization)的收敛性,引入了选择机制;同时为了平衡PSO算法的全局搜索能力和局部改良能力,提出了一种构造惯性权重的方法。以160 MW燃油锅炉汽轮发电机组动态模型为例,进行实例仿真,所得结果验证了本算法的实用性、有效性。
The improved particle swarm algorithm has been used in the multi-objective optimization of unit coordinate control case study.In order to enhance the convergent behavior of the PSO algorithm（Particle swarm Optimization）,the selection mechanism has been introduced;In order to balance the global search ability and local improved ability of the PSO algorithm,a building method of inertia weight has been put forward.Taking the power unit dynamic model of a 160MW oil fired drum-type boiler-turbine-generator unit as an example,the simulation results show that the algorithm is effective and practical.
出处
《电力科学与工程》
2011年第10期53-56,共4页
Electric Power Science and Engineering
关键词
改进粒子群算法
火电机组
多目标优化
协调控制
improved particle swarm optimization
thermal power unit
multiobjective optimization
coordinate
