对计及经济、环境因素的电力系统发电调度问题(Economic Environmental Dispatching,EED)进行研究,提出一种采用改进多目标灰狼算法的发电调度规划方案.构建基于发电燃料成本、污染气体排放量和节点电压偏移量等指标的多目标EED模型,并采用改进的多目标灰狼算法进行求解,以得到更优的Pareto前沿和折中解.设计多度量自适应FCM算法对灰狼算法(Gray Wolf Algorithm,GWA)种群多样性进行分析,重新定义狼群层级结构和Pareto前沿规模控制策略,并在此基础上提出反向学习和变异进化策略,以提升GWA全局收敛性能.仿真结果表明,改进的GWA具有优秀全局寻优能力,而且基于改进多目标灰狼算法得到的Pareto前沿和折中解更具可行性和优越性.
Power System Dispatching Planning Using Improved Multi-Objective Grey Wolf Algorithm
The economic environmental dispatching(EED)of power system considering economic and environmental factors is stud-ied,and a generation dispatching planning scheme based on improved multi-objective Gray Wolf algorithm is proposed.The multi-objective EEDmodel based on power generation fuel cost,pollutant gas emission and node voltage offset is constructed,and the im-proved multi-objective Gray Wolf Algorithm(GWA)is used to obtain a better Pareto front and compromise solution.The multi met-ric adaptive FCM algorithm is designed to analyze the population diversity of GWA.The hierarchical structure of wolves are rede-fined,and reverse learning and mutation evolution strategies are proposed to improve the global convergence performance of GWA.The simulation results show that the improved GWA has excellent global optimization ability,and the Pareto frontier and compromise solutions based on the improved multi-objective Gray Wolf Algorithm are more feasible and superior.
Generation DispatchingParetoMulti-ObjectiveGray Wolf AlgorithmFCMCompromise Solution
万方数据
维普
