一种需求响应参与下风电储能系统调度方法的研究  

Research on Two-stage Scheduling of Wind Energy Storage System with Demand Response Participation

作　　者：何平[1] 迟福建 赵志斌[2] 刘聪[1] 李桂鑫[1] 王哲[1] HE Ping;CHI Fujian;ZHAO Zhibin;LIU Cong;LI Guixin;WANG Zhe(State Grid Tianjin Electric Power Company,Tianjin 300184;North China Electric Power University,Beijing 102206)

机构地区：[1]国网天津市电力公司,天津300184 [2]华北电力大学,北京102206

出　　处：《计算机与数字工程》2021年第9期1936-1940,共5页Computer & Digital Engineering

摘　　要：针对风电并网对电力系统稳定性的不利影响,论文将储能系统和需求响应引入含风电的电网优化调度中。首先以系统最低发电成本为调度目标,以日前预测和实时风能预测作为随机变量,将需求响应和储能系统分别引入需求侧和发电侧,同时通过两阶段调度,构建风电储能系统的两阶段调度优化模型。其次利用粒子群优化算法对模型进行求解。应用场景分析的结构表明,所提调度方法采用粒子群优化算法可以较好求得模型的全局最优解;通过储能系统和需求响应的引入可以提高主动配电网的风电利用效率,降低发电成本。In view of the adverse effects of wind power grid-connected on power system stability,this paper introduces energy storage system and demand response into grid-optimized dispatch with wind power.Firstly,the minimum power generation cost of the system is used as the scheduling target.The daily forecast and real-time wind energy prediction are used as random variables.The demand response and energy storage system are introduced into the demand side and the power generation side respectively.At the same time,combined with the two-stage optimization theory,the wind power and energy storage are built.The two-stage scheduling optimization model of the system.Secondly,the particle swarm optimization algorithm is used to solve the model.The structure of the application scenario analysis shows that the proposed scheduling method can obtain the global optimal solution of the model by using the particle swarm optimization algorithm.The introduction of the energy storage system and the demand response can improve the wind power utilization efficiency of the active distribution network and reduce the cost of power generation.

关 键 词：需求响应 储能系统 风能 两阶段调度 粒子群优化算法 

分 类 号：TM769[电气工程—电力系统及自动化]