The Power Grid Probabilistic Vulnerability Evaluation Considering the Stochastic Perturbations of Wind Farm

2017 2nd Asia Conference on Power and Electrical Engineering

能源学;电工学

Liu, Qunying^1 ; Zhao, Renguang^1 ; Chen, Shuheng^2 ; Liu, Ruihua^3 ; Zhang, Changhua^2

School of Automation, University of Electronic Science and Technology of China, Chengdu, Sichuan

611731, China^1

School of Energy Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan

611731, China^2

Sichuan Electric Vocational and Technical College, Chengdu, Sichuan, China^3

关键词: K-Means clustering algorithm;    New evaluation methods;    Probabilistic modeling;    Stochastic perturbations;    Stochastic volatility;    Three parameter Weibull distribution;    Vulnerability evaluations;    Wind turbine generator systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/199/1/012028/pdf
DOI  :  10.1088/1757-899X/199/1/012028

来源: IOP

【 摘 要 】

Considering the stochastic volatility of load and wind farm, stochastic outage rate of generator, based on the combination of Cumulant and Gram-Charlier series (CGC), a new evaluation method for probabilistic vulnerability of transmission network is proposed. Firstly, the three-parameter Weibull distribution is adapted to describe the random variation of wind speed and the probabilistic model for wind turbine generator system is established. And then, in order to avoid complicating convolution and improve the computational speed, the vulnerability index of nodes and branches in power grid is proposed with the combination of Cumulant and Gram-Charlier series. Furthermore, the K-means clustering algorithm is adapted to evaluate the vulnerability of nodes and branches. The simulation results in IEEE30 bus system show that the proposed method can lead to a reliable and effective evaluation result.