基于INMOPSO的含水风光电力系统优化调度研究  

Study on Optimal Dispatch of Power System with Hydro,Wind and Solar Power Stations Based on INMOPSO

作　　者：赵亚威 纪昌明[1] 张验科[1] 马秋梅 孟长青 ZHAO Yawei;JI Changming;ZHANG Yanke;MA Qiumei;MENG Changqing(School of Water Resources and Hydropower Engineering,North China Electric Power University,Beijing 102206,China)

机构地区：[1]华北电力大学水利与水电工程学院,北京102206

出　　处：《水力发电》2021年第4期117-121,共5页Water Power

基　　金：国家自然科学基金资助项目(51709105,41901028);中央高校基本科研业务费专项资金资助(2020MS026);中国博士后科学基金资助项目(2020M680487)。

摘　　要：考虑水风光可再生能源消纳受阻问题,以运行成本最小和水风光弃电量最小为目标建立了电力系统多目标优化调度模型。运用多目标法改进约束条件处理方式,采用马氏距离改进适应值计算方式,提出了改进小生境多目标粒子群算法。实例计算结果表明,改进算法的近似Pareto前沿、算法收敛性和解分布的均匀性均优于对比算法,最佳均衡解的运行成本和弃电量也均小于对比算法,改进策略可行有效。Considering the consumption ability of power system on renewable energy,a multi-objective optimal dispatch model of power system is established with minimum operation cost and minimum abandoned power.The Improved Niche Multi-objective Particle Swarm Optimization Algorithm(INMOPSO)is proposed,which uses the multi-objective method to improve the treatment of constraint condition,and uses Mahalanobis distance to replace the Euclidean distance to improve the calculation of fitness value.The example calculation results of multi-objective optimal dispatching model of power system show that,the approximate Pareto front,the convergence and the uniformity of solution distribution of INMOPSO are all better than those of contrast algorithms,the operating cost and abandoned power of the optimal equilibrium solution are lower than those of contrast algorithms,and the improvement strategy is feasible and effective.

关 键 词：可再生能源 弃电量 电力系统优化调度 改进粒子群算法 多目标法 马氏距离 

分 类 号：TM715[电气工程—电力系统及自动化]