多信息特征粒子群优化算法的动态经济负荷分配  

Study of Dynamic Economic Load Dispatch Using Particle Swarm Optimization with Multi-information Characteristics

作　　者：黄松[1] 王艳[1] 纪志成[1,2] 

机构地区：[1]江南大学物联网工程学院,无锡214122 [2]江南大学物联网技术应用教育部工程研究中心,无锡214122

出　　处：《系统仿真学报》2017年第9期2159-2167,共9页Journal of System Simulation

基　　金：国家自然科学基金(61572238);江苏省杰出青年基金(BK20160001)

摘　　要：根据发电系统的特点,考虑多燃料和24 h预测负荷需求数据,建立了一种动态经济负荷分配的优化模型,提出了一种基于个体最优位置的多信息特征粒子群优化算法求解该问题。定义了质心位置和中值位置,采用了由个体最优位置,质心位置和中值位置构成新的速度更新公式。减少了求解复杂优化问题时的早熟现象,能够有效地解决求解动态经济负荷分配问题。通过对算例DED1的实验仿真,表明该算法能够有效求解DED问题,具有更好的优化性能。According to the characteristics of power system, an model of dynamic economic load dispatch based on multiple fuel resources and 24-hour forecasting load demand was established, and a particle swarm optimizer using multi-information characteristics of all personal-best information was proposed to solve it. In the algorithm, centroid position and median position were defined, and then the personal-best position, centroid position and median position was developed to modify the velocity update formula. The algorithm could reduce the premature phenomenon for solving complex optimization problems, and it could make effectively solve dynamic economic load dispatch. The simulation was conducted to optimize DED1 instance, and the results show that the algorithm can effectively solve the problem and has a better performance.

关 键 词：粒子群优化算法 经济负荷分配 信息特征 电力系统 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TM85[自动化与计算机技术—控制科学与工程]