Stochastic Modeling and Small Signal Stability Analysis of Wind Power System Based on Markov Theory

被引：0
|
作者：
Wang J. [1 ]
Sun Y. [1 ]
Zhai S. [1 ]
Wei Z. [1 ]
Sun G. [1 ]
机构：
[1] College of Energy and Electrical Engineering, Hohai University, Nanjing, 210098, Jiangsu Province
来源：
Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 02期
基金：
中央高校基本科研业务费专项资金资助; 中国国家自然科学基金;
关键词：
Markov theory; Stochastic differential equations; Stochastic stability; Wind power fluctuations;
D O I：
10.13335/j.1000-3673.pst.2018.0745
中图分类号：
学科分类号：
摘要：
With continuous scale expansion of wind power integration, random characteristics of power system are more and more prominent due to volatility and intermittency of wind energy. Traditional deterministic analysis methods and stochastic differential equation methods are difficult to accurately analyze wind power system stability. In this paper, based on stochastic ordinary differential equations, Markov theory is utilized to establish a stochastic Markov dynamic model of wind power systems to analyze stochastic small signal stability. Then, based on the developed system model, Lyapunov energy function and M matrix are combined to present the analytical method of stochastic mean and mean square stability for wind power system under multiple operating conditions. Compared with conventional stochastic differential equation analysis method, the proposed method can overcome the shortcomings that small signal stability cannot be analyzed when system operating conditionschange. Simulation results verify validity and correctness ofthe proposed method. © 2019, Power System Technology Press. All right reserved.
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页码：646 / 654
页数：8
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