Power System Transient Stability Preventive Control Based on Deep Cross Network

被引:2
|
作者
Zhou, Bo [1 ]
Wang, Kangkang [1 ]
Wei, Wei [1 ]
Chen, Zhen [1 ]
Jin, Dan [1 ]
Ye, Xi [2 ]
Liu, Junyong [3 ]
Li, Linxiu [3 ]
机构
[1] State Grid Sichuan Elect Power Res Inst, Chengdu, Peoples R China
[2] State Grid Sichuan Elect Power Co, Chengdu, Peoples R China
[3] Sichuan Univ, Coll Elect Engn, Chengdu, Peoples R China
关键词
Transient Stability Assessment; Preventive Control; Deep Learning; Deep Cross Network; Transient Stability Constrained Optimal Power Flow; Successive Linear Programming;
D O I
10.1109/ICPSAsia55496.2022.9949743
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Online transient stability assessment and preventive control are important measures to prevent power system blackouts. Based on the deep cross network (DCN), an online assessment and preventive control method for power system transient stability is proposed. The deep cross network is developed to estimate the critical clearing time (CCT) of the credible fault contingencies. Based on the deep cross network model, the sensitivity of the active power of the generator set to the fault critical clearing time is calculated and then the DCN model-embedded transient stability constrained optimal power flow (TSCOPF) model is proposed to compute the preventive generation re-dispatch strategy. This TSCOPF model is computed by successive linear programming assisted by the DCN. The simulation results of the IEEE 39-bus test system show that this method can give early warning to the operation mode with instability risk and generate preventive control strategies, which can effectively improve the safety level of power grid operation.
引用
收藏
页码:1586 / 1591
页数:6
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