scholarly journals Operation Risk Assessment of Power System With High Risk Wind Power Ramping

Author(s):  
Xinyuan Tong ◽  
Hongtao Wang
Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 464
Author(s):  
Qingwu Gong ◽  
Si Tan ◽  
Yubo Wang ◽  
Dong Liu ◽  
Hui Qiao ◽  
...  

In order to solve the problem of the inaccuracy of the traditional online operation risk assessment model based on a physical mechanism and the inability to adapt to the actual operation of massive online operation monitoring data, this paper proposes an online operation risk assessment of the wind power system of the convolution neural network (CNN) considering multiple random factors. This paper analyzes multiple random factors of the wind power system, including uncertain wind power output, load fluctuations, frequent changes in operation patterns, and the electrical equipment failure rate, and generates the sample data based on multi-random factors. It uses the CNN algorithm network, offline training to obtain the risk assessment model, and online application to obtain the real-time online operation risk state of the wind power system. Finally, the online operation risk assessment model is verified by simulation using the standard network of 39 nodes of 10 machines New England system. The results prove that the risk assessment model presented in this paper is more rapid and suitable for online application.


2015 ◽  
Vol 30 (3) ◽  
pp. 1359-1368 ◽  
Author(s):  
Michael Negnevitsky ◽  
Dinh Hieu Nguyen ◽  
Marian Piekutowski

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 900
Author(s):  
Shiwei Xia ◽  
Liangyun Song ◽  
Yi Wu ◽  
Zhoujun Ma ◽  
Jiangping Jing ◽  
...  

Large-scale wind power integrated into power grids brings serious uncertainties and risks for power system safe operation, and it is imperative to evaluate power system security risk pertinent to high-level of uncertainties. In this paper, a comprehensive source–network–load probabilistic model, representing the typical uncertainties penetrated in power generation transmission consumption portion, is firstly set for power system operation. Afterwards an integrated LHS–CD approach based on the Latin hypercube sampling (LHS) and Cholesky decomposition (CD) is tailored to effectively conduct the security risk assessment, in which the LHS is utilized to stratified sample the uncertainties of wind power and thermal power, transmission line outage, and load demands, while the CD part is adopted to address the correlations of uncertainties by rearranging the sampled matrix generated by LHS. Moreover, static voltage risk and transmission line overloaded risk index are properly defined for quantitatively evaluating power system operational security risk. Simulation results of a modified New England 39-bus system confirm that the proposed integrated LHS–CD approach is effective and efficient for power system security risk assessment with consideration of source–network–load demand uncertainties.


2016 ◽  
Vol 10 (2) ◽  
pp. 359-365 ◽  
Author(s):  
Weisi Deng ◽  
XiangNing Lin ◽  
Hongfa Ding ◽  
Pei Bie ◽  
Jiasi Wu ◽  
...  

Energies ◽  
2018 ◽  
Vol 11 (4) ◽  
pp. 727 ◽  
Author(s):  
Zhe Zhang ◽  
Hang Yang ◽  
Xianggen Yin ◽  
Jiexiang Han ◽  
Yong Wang ◽  
...  

2014 ◽  
Vol 672-674 ◽  
pp. 355-360
Author(s):  
Hui Ren ◽  
Jia Qi Fan ◽  
David Watts ◽  
Dan Wei

With large-scale wind power integrates into power system, the risk brought by the uncertainty of wind power output can no longer be neglected. Under this circumstance, the operation risk due to the uncertainty of wind generation and the contribution of wind power to energy conservation and emission reduction are quantified, and the corresponding quantified operational cost, environmental cost and operation risk are being integrated into the economic dispatching model to establish a multi-objective optimization dispatch model. Non-dual interior point method is used to solve the optimization problem. The method is applied to Hebei Southern power grid, simulated with actual wind power output data of one typical day. Simulation results show the rationality and effectiveness of the proposed method.


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