考虑需求侧管理的光伏微电网多目标优化调度方法  

MULTI-OBJECTIVE OPTIMIZATION SCHEDULING METHOD FOR PHOTOVOLTAIC BASED MICROGRID CONSIDERING DEMAND SIDE MANAGEMENT

作　　者：禹威威 刘世林[1] 陈其工[1] 张春[1] 

机构地区：[1]检测技术与节能装置安徽省重点实验室(安徽工程大学),芜湖241004

出　　处：《太阳能学报》2017年第11期2972-2981,共10页Acta Energiae Solaris Sinica

基　　金：安徽省自然科学基金(1508085ME74);安徽省教育厅自然科学重大项目(KJ2015ZD06);安徽工程大学博士科研启动基金(S031502001)

摘　　要：针对考虑需求侧管理(DSM)的光伏微电网优化调度问题开展研究。首先,在对典型光伏微电网结构和运行状态进行简要分析的基础上,以系统总运行费用和储能循环电量最小为目标,综合考虑功率平衡、储能系统荷电状态(SOC)、负荷可转移的时间范围等约束条件,建立在分时电价和DSM机制下的光伏微电网多目标优化模型;其次,针对模型具有多目标、多约束和非线性等特点,提出基于非支配排序遗传算法(NSGA-II)的优化求解策略。最后,在Matlab平台上对不同场景下的具体算例进行仿真分析,获得光伏微电网优化调度问题的多组Pareto最优解集。通过分析不同日照条件下的典型调度方案,验证优化模型的合理性和有效性。The optimization scheduling method for photovoltaic based microgrid（PV-MG）considering demand sidemanagement（DSM） is investigated in this paper. Firstly,based on the brief analysis of typical configuration andoperation states of PV-MG,the multi-objective optimization scheduling model with the objectives of minimizing the totaloperation cost and the energy circulation of energy storage system（ESS）,is established. In the model,the mechanisms ofunder time of use（TOU）and DSM are applied,and the constraints of the power balance,the state of charge（SOC）ofESS,and the allowed time range of transferable loads are all considered comprehensively. Then,focusing on thecharacteristics of optimization model,such as multi-objective,multi-constraint,and nonlinearity,non-dominatedsorting genetic algorithm-II（NSGA-II）based solving strategy is proposed. Finally,simulation cases under differentconditions are analyzed in Matlab,several Pareto solution sets are obtained. By analyzing the typical scheduling schemesunder different solar radiations,the rationality and effectiveness of the established optimization model are verified.

关 键 词：光伏微电网 需求侧管理 多目标优化 优化调度 非支配排序遗传算法 

分 类 号：TM732[电气工程—电力系统及自动化]