Sequential steady-state security region-based transmission power system resilience enhancement

2021 ◽  
Vol 151 ◽  
pp. 111533
Author(s):  
Chong Wang ◽  
Ping Ju ◽  
Feng Wu ◽  
Shunbo Lei ◽  
Xueping Pan
2012 ◽  
Vol 516-517 ◽  
pp. 1332-1336
Author(s):  
Zhong Cheng Li ◽  
Bu Han Zhang ◽  
Cheng Xiong Mao ◽  
Kui Wang

With the proportion of the installed capacity of wind farm in the grid increasing, the impact of wind farm on the power system security becomes obvious. The steady-state security analysis is one of the important measures to improve the power system security. Based on DC flow, considering the available transmission capability limit, the paper chooses the biggest security region volume as objective function with the upper and lower limits of security region multi-dimensional cuboid being as control variables, which transforms the maximum steady-state security region into nonlinear programming problem with linear constraints. This not only includes the biggest points for the safe operation, but also the order expansion problem doesn’t exist. Then Lagrange-Quasi-Newton is used to solve the equation, and the analysis of the example proves the feasibility of the proposed model and algorithm. Then we assume that wind speed distribution is weibull distribution, so we can assess the safe operation probability of wind power.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 139221-139243
Author(s):  
Zhengguang Zhu ◽  
Jun Yan ◽  
Chen Lu ◽  
Zhong Chen ◽  
Jiang Tian

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 148
Author(s):  
Lili Wu ◽  
Ganesh K. Venayagamoorthy ◽  
Jinfeng Gao

Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.


Author(s):  
Laiz Souto ◽  
Joshua Yip ◽  
Wen-Ying Wu ◽  
Brent Austgen ◽  
Erhan Kutanoglu ◽  
...  

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