Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Revisiting Capacity Value of Variable Renewable Energy Generation in Power Systems with High Renewable Energy Penetration
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1.State Key Laboratory of Power System Operation and Control, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China;2.State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing 400044, China;3.Department of Electrical and Electronic Engineering, Imperial College London, SW7 2BU, London, U.K.;4.China Electric Power Planning & Engineering Institute, Beijing 100120, China

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This work was supported in part by the National Key R&D Program of China (No. 2022YFB2403300), in part by the Scientific & Technical Project of State Grid Shanghai Electric Power Company (No. SGSHDK00DWJS2310470), and in part by the Scientific & Technical Project of China Electric Power Planning & Engineering Institute (No. K202316).

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    Abstract:

    Adequacy is a key concern of power system planning, which refers to the availability of sufficient facilities to meet demand. The capacity value (CV) of variable renewable energy (VRE) generation represents its equivalent contribution to system adequacy, in comparison to conventional generators. While VRE continues to grow and increasingly dominates the generation portfolio, its CV is becoming non-negligible, with the corresponding impact mechanisms becoming more complicated and nuanced. In this paper, the concept of CV is revisited by analyzing how VRE contributes to power system balancing at a high renewable energy penetration level. A generalized loss function is incorporated into the CV evaluation framework considering the adequacy of the power system. An analytical method for the CV evaluation of VRE is then derived using the statistical properties of both hourly load and VRE generation. Through the explicit CV expression, several critical impact factors, including the VRE generation variance, source-load correlation, and system adequacy level, are identified and discussed. Case studies demonstrate the accuracy and effectiveness of the proposed method in comparison to the traditional capacity factor-based methods and convolution-based methods. In the IEEE-RTS79 test system, the CV of a 2500 MW wind farm (with 40% renewable energy penetration level) is found to be 6.8% of its nameplate capacity. Additionally, the sensitivity of CV to various impact factors in power systems with high renewable energy penetration is analyzed.

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History
  • Received:October 05,2024
  • Revised:January 07,2025
  • Adopted:
  • Online: September 17,2025
  • Published:
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