1.Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;2.State Key Laboratory of Power System Operation and Control, Tsinghua University, Beijing 100084, China

The penetration of high-proportion renewable energy brings significant volatility and uncertainty to power grids. Thus the receiving end of the power system faces the problem of insufficient adjustable resource capacity. It requires the full utilization of a large number of flexible energy resources to participate in power system dispatch and provide auxiliary services. However, the vast number, wide distribution, and diverse characteristics of these flexible energy resources pose significant challenges to centralized dispatch and control. It is necessary to manage and dispatch these flexible energy resources in a clustered way. To accurately assess the role of clusters in the power system dispatch and control, it is essential to aggregate these flexible energy resources and evaluate their performance by using appropriate quantitative metrics based on application requirements. According to the application demands of flexible resource clusters in power system dispatch and electricity market, a quantitative metric system of flexibility for evaluating the adjustable capacity of flexible energy resource clusters is proposed. Based on their physical characteristics, these resources are categorized into three types: generator-like characteristics, storage-like characteristics, and common characteristics. For quantitative evaluation of the cluster flexibility metrics across various application scenarios, an aggregation reference model comprising an equivalent generator and an equivalent energy storage is proposed. This aggregation reference model has a clear physical interpretation, exhibits nested properties, and therefore is suitable for various time scales and energy forms. It can be used to calculate the quantitative metrics for specific application scenarios and widely applied in scenarios such as asynchronous dispatch of distributed energy resource clusters, joint optimization dispatch of integrated energy systems, and participation of virtual power plant in electricity market bidding.

This work is supported by National Key R&D Program of China (Key Techniques of Adaptive Grid Integration and Active Synchronization for Extremely High Distributed Photovoltaic Power Penetration Generation, No. 2022YFB2402900) and National Natural Science Foundation of China (No. U2066601).