基于改进粒子群算法的智能电力调度自动化主站电机组的调度方法  

An Improved Particle Swarm Optimization Based Scheduling Method for the Main Station of Intelligent Power Scheduling Automation

作　　者：林展华 LIN Zhanhua(Beijing Kedong Power Control System Co.,Ltd.,Beijing 100192,China)

机构地区：[1]北京科东电力控制系统有限责任公司,北京100192

出　　处：《通信电源技术》2023年第17期1-3,共3页Telecom Power Technology

摘　　要：为控制电机组的发电成本,研究一种新的基于改进粒子群优化(Particle Swarm Optimization,PSO)算法的智能电力调度自动化主站电机组的调度方法。将经济成本最小化作为目标,建立电机组调度目标函数;引进改进的PSO算法,将主站的节点作为粒子,将电机组优化调度过程作为空间中的粒子寻优过程,计算电机组调度最优解;在粒子群中加入惯性系数,将此系数作为约束,控制粒子的更新或飞行速度,以此实现电机组调度方案的全局寻优。实验结果表明,提出的电机组调度方法应用效果良好,规范使用所提方法调度电机组,可以有效降低经济成本,为发电企业的市场运营创造更高的价值与经济效益。In order to control the power generation cost,a new scheduling method of intelligent power dispatching automation main station based on improved Particle Swarm Optimization(PSO)is studied.Taking the economic cost minimization as the goal,the scheduling objective function is established.The improved PSO algorithm is introduced to calculate the optimal solution of the unit scheduling by taking the node of the main station as the particle and the unit optimization scheduling process as the particle optimization process in space.The inertia coefficient is added to the particle swarm and used as a constraint to control particle renewal or flight speed,so as to realize the global optimization of the generator scheduling scheme.The experimental results show that the proposed generator scheduling method has good application effect.The proposed method can effectively reduce the economic cost and create higher value and economic benefits for the market operation of power generation enterprises.

关 键 词：电机组调度 改进粒子群优化(PSO)算法 自动化 电力调度 

分 类 号：TM734[电气工程—电力系统及自动化]