Risk Assessment of Small-signal Instability for Renewable Power System Based on High-dimensional Model Representation Method

被引：0
|
作者：
Zhou Y. [1 ]
Sun J. [1 ]
Wang S. [1 ]
Hao Y. [1 ]
Liu C. [2 ]
机构：
[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding
[2] Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2022年 / 46卷 / 14期
关键词：
high-dimensional model representation method; moving least squares method; renewable energy; small-signal stability; uncertainty;
D O I：
10.7500/AEPS20210806006
中图分类号：
学科分类号：
摘要：
Affected by the large number and complex probability distribution of random variables in the power system with renewable energy, the risk assessment of small-signal instability faces challenges in terms of efficiency and accuracy. Therefore, this paper proposes a risk assessment approach of small-signal instability for power systems with renewable energy based on the high-dimensional model representation method. First, the kernel density estimation method is used to construct the probability distribution model for single variable, and the Pair-Copula function model is used to construct the joint distribution model of high-dimensional correlation variables, which characterizes complex probability distribution of variables. Then, a risk assessment method of small-signal instability based on moving least squares method and high-dimensional model representation method is proposed, and the modeling efficiency is improved through sparse approximation to the nonlinear coupled correlation variables. According to the characteristic of the actual probability distribution of wind, irradiance and load, a sampling method combined with probability is proposed to improve the calculation accuracy. Finally, by using the 2-area 4-machine system and the New England-New York 16-machine system with access of renewable energy as examples for analysis, the accuracy and the efficiency of the proposed method are verified. © 2022 Automation of Electric Power Systems Press. All rights reserved.
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页码：73 / 82
页数：9
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