• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

ELECTRIC POWER CONSTRUCTION ›› 2022, Vol. 43 ›› Issue (5): 137-144.doi: 10.12204/j.issn.1000-7229.2022.05.015

• New Energy Power Generation • Previous Articles    

Grid-Connection Performance Evaluation of Renewable Energy Station under Distributed Framework

YANG Libin1,2(), ZHANG Lei3, LIU Yanzhang3, LI Zhengxi2, ZONG Ming1   

  1. 1. School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
    2. Clean Energy Development Research Institute of State Grid Qinghai Electric Power Company, Xining 810000, China
    3. China Electric Power Research Institute, Nanjing 210003, China
  • Received:2022-01-24 Online:2022-05-01 Published:2022-04-29
  • Contact: YANG Libin E-mail:254824088@qq.com
  • Supported by:
    Major Science and Technology Project of Qinghai Province(2018-GX-A6);Science and Technology Project of State Grid Qinghai Electric Power Company(522830190017)


Under the background of new power systems dominated by renewable energy, it is necessary to grasp the grid-connection performance of renewable energy station in real time. Firstly, grid-connection performance evaluation of renewable energy station under distributed framework is proposed in this paper, and the application platform architecture under this framework is designed by introducing edge computing idea. Then, the index system for grid-connection performance evaluation of renewable power station is established and the calculation methods for key parameters are given. Finally, an application example of frequency response capability evaluation is presented. The practice shows that the PLL method has certain advantages in accuracy and convergence for frequency parameter estimation. In addition, because of the advantages in data accuracy, remote communication and computing efficiency, the idea of distributed evaluation can provide a solution for panoramic monitoring and control of renewable energy stations.

Key words: grid-connected performance assessment, renewable energy station, distributed framework, edge computing

CLC Number: