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

doi:10.12204/j.issn.1000-7229.2022.05.015

Abstract

Abstract:

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:

TM732

YANG Libin, ZHANG Lei, LIU Yanzhang, LI Zhengxi, ZONG Ming. Grid-Connection Performance Evaluation of Renewable Energy Station under Distributed Framework[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(5): 137-144.

Figures/Tables 10

Fig.1 Distributed framework of grid-connection performance evaluation for renewable energy station

Fig.2 Architecture of application platform

Fig.3 Interface of application platform

Fig.4 Index system of grid-connection performance evaluation for renewable energy station

Fig.5 Evaluation method for grid-connection performance of renewable energy station

Fig.6 Diagram for evaluation of active power control

Fig.7 Frequency estimation based on DFT

Fig.8 Comparison for results of frequency estimation

Table 1 Evaluation results of fast frequency response capability

Fig.9 Curve of virtual rotary inertia response

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