Stochastic small disturbance stability analysis of nonlinear power system

被引：0

作者：

Xu, Wenbi ^{[1
]}

Wang, Jie ^{[1
]}

机构：

[1] School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Minhang District, Shanghai

来源：

Dianwang Jishu/Power System Technology | 2014年 / 38卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Nonlinear; Power system; Stability; Stochastic differential equation;

D O I：

10.13335/j.1000-3673.pst.2014.10.018

中图分类号：

学科分类号：

摘要：

Power system is a nonlinear system with many random disturbances. In recent years, the development of electric power industry has caused more and more stochastic factors of the network. The traditional deterministic analysis methods can no longer meet the requirements. Therefore, it has important value of theory and application to apply the thought and method of stochastic system to power system by full analysis of the random disturbance characteristics of power system, and to establish more precise mathematics model of power system and analyze stability of power system. Aimed at external random excitation, the model of non-linear system with random disturbance was constructed and the result that the system is mean stable and mean square stable under stochastic small disturbance was proved in this paper. Euler-Maruyama (EM) algorithm was used to simulate the stability of new England 10 generator 39 bus system, the response trajectories under different random excitation intensity were analyzed, and the stability theory of power system was validated by the simulation results in this paper.

引用

页码：2735 / 2740

页数：5

共 17 条

[1]

Peng Y., Deng F., A survey on power system stochastic stability analysis and control, Advanced Technology of Electrical Engineering and Energy, 26, 3, pp. 52-58, (2007)

[2]

Papaefthymiou G., Verboomen J., Schavemaker P.H., Et al., Impact of stochastic generation in power systems contingency analysis, 9th International Conference on Probabilistic Methods Applied to Power Systems, (2006)

[3]

De Marco C.L., Bergen A.R., A security measure for random load disturbances in nonlinear power system models, 34, 12, pp. 1546-1557, (1987)

[4]

Long J., Mo Q., Zeng J., A stochastic programming based short-Term optimization scheduling strategy considering energy conservation for power system containing wind farms, Power System Technology, 35, 9, pp. 133-138, (2011)

[5]

Guo X., Xie K., Hu B., Et al., A time-interval based probabilistic production simulation of power system with grid-connected photovoltaic generation, Power System Technology, 37, 6, pp. 1499-1505, (2013)

[6]

Wang K.W., Chung C.Y., Tse C.T., Et al., Improved probabilistic method for power system dynamic stability studies, 147, 1, pp. 37-43, (2000)

[7]

Hiskens I.A., Alseddiqui J., Sensitivity, approximation, and uncertainty in power system dynamic simulation, 21, 4, pp. 1808-1820, (2006)

[8]

Zhang J., Ju P., Yu Y., Et al., Response and stability of power system in Gauss small random excitation, China Science: Science and Technology, 42, 7, pp. 851-857, (2012)

[9]

Milano F., Zarate-Minano R., A systematic method to model power systemsas stochastic differential algebraic equations, 28, 4, pp. 4537-4544, (2013)

[10]

Xiao K., Guo Y., Effects of stochastic load model on power system voltage stability, 40, 9, pp. 9-12, (2000)

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