摘要
在综合对比用于循环水系统轴功率优化模型的2种不同粒子群优化算法的基础上,提出用服从均匀分布惯性权重的粒子群优化算法求解轴功率优化问题,得到了最优决策向量。该算法能够有效地找到循环水系统中循环水泵的最优组合和最佳调速比,使水泵在高效区内运行,提高系统的运行效率。与遗传算法相比,其实现简单,收敛速度快,并有更好的全局收敛特性和更小的系统误差。
On the basis of comprehensive comparison between two different particle swarm optimization（PSO） algorithms applied to optimization model of shaft power for circulating water system,a PSO algorithm with stochastic inetia weight has been put forward for seeking solution of problem to optimize the shaft power,obtaining the optimal decision vector.The said method can effectively seek the optimal combination of circulating water pumps in the circulating water system and the best speed-regulating ratio,making the water pump to work in high effective region,enhancing efficiency in operation of the system.Compared with the genetic algorithm,the PSO algorithm is simple in realization,boasting quick converging speed,as well as more better whole convergence behavior and more smaller systematic error.
出处
《热力发电》
CAS
北大核心
2010年第7期65-68,共4页
Thermal Power Generation
基金
国家863项目资助(2007AA05Z232)
浙江省科技计划资助(2007C21180)
关键词
火电厂
循环水泵
粒子群优化算法
随机惯性权重
遗传算法
轴功率
thermal power plant
circulating water pump
PSO algorithm
stochastic inertia weight
genetic algorithm
shaft power
