蒋松含, 张沛超, 张宇, 黄宏声. 集成大规模需求响应资源的智能电网数字实时协同仿真方法[J]. 电力系统自动化, 2017, 41(9): 130-136.
引用本文: 蒋松含, 张沛超, 张宇, 黄宏声. 集成大规模需求响应资源的智能电网数字实时协同仿真方法[J]. 电力系统自动化, 2017, 41(9): 130-136.
JIANG Songhan, ZHANG Peichao, ZHANG Yu, HUANG Hongsheng. Digital Real-time Co-simulation Method of Smart Grid for Integrating Large-scale Demand Response Resources[J]. Automation of Electric Power Systems, 2017, 41(9): 130-136.
Citation: JIANG Songhan, ZHANG Peichao, ZHANG Yu, HUANG Hongsheng. Digital Real-time Co-simulation Method of Smart Grid for Integrating Large-scale Demand Response Resources[J]. Automation of Electric Power Systems, 2017, 41(9): 130-136.

集成大规模需求响应资源的智能电网数字实时协同仿真方法

Digital Real-time Co-simulation Method of Smart Grid for Integrating Large-scale Demand Response Resources

  • 摘要: 激活负荷侧资源的需求响应(DR)潜力是目前智能电网的重要研究课题,但DR资源所具有的海量、多样和互动特点给实时仿真带来了巨大挑战。文中提出了一种集成大规模快速DR资源的智能电网数字实时协同仿真方法。首先,选择解耦点将包含DR资源的电网进行分区解耦,依据动态响应的不同进行多速率仿真。其次,设计了包含双向控制的接口算法以构成协同仿真。然后,分别分析了数字实时协同仿真在微网和高压电网中的典型应用,并采用RTDS和GridLAB-D给出了仿真系统的具体构成。最后,以大规模空调负荷为例验证了所提协同仿真方法的有效性,该方法可以利用通用计算机扩展现有数字实时仿真系统对大规模快速DR资源的仿真能力,具有良好的可扩展性与经济性。

     

    Abstract: Activating the vast potentials of demand response(DR)in loads is currently an important research topic of the smart grid.However,because of the characteristics of mass,diversity and responsiveness of DR resources,it is a huge challenge to incorporating the DR resources in real-time simulation.A digital real-time co-simulation method of the smart grid for integrating large-scale fast DR resources is proposed.First,the network with a large number of DR resources is decoupled from the rest of the grid,which asks for building the multi-rate digital simulation according to different dynamic responses.Then,an interface algorithm including loop control is designed for the co-simulation.After that,typical application scenarios about microgrid and high-voltage grid are analyzed,and constitutions of the digital real-time co-simulation system are given based on RTDS and GridLAB-D.Finally,by taking the large-scale air-conditioning load as an example,the effectiveness of the proposed co-simulation method is verified.By using personal computers,the method is able to extend the simulation ability of existing digital real-time simulation systems for large-scale fast DR resources,which shows the good scalability and economic benefits of the proposed method.

     

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