Emergency control strategy of power system transient instability based on DBN. Issue 1 (January 2021)

• Record Type: Journal Article
• Authors: Qiang, Ziyue; Wu, Junyong; Li, Baoqin; Zhang, Ruoyu; Qin, Liuyun
• Is Part Of: IOP conference series. Volume 645:Issue 1(2021)
• Publication Date: 2021-01
• Subjects: Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/645/1/012016
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: In order to satisfy the real-time emergency control decision-making after power system transient instability, an emergency control strategy based on deep belief network is proposed in this paper. Firstly, the DBN instability degree prediction model is established to fit the mapping relationship between generator power angle characteristics and transient stability coefficient; secondly, according to the fitting instability degree index, the sensitivity of generator tripping is solved to determine the generator tripping control action bus; finally, according to the emergency control optimization model and transient stability constraints, the optimal generator tripping strategy is solved and verified in New England 10-machine and 39-node system. The results show that the proposed method has high prediction accuracy and efficiency, which can make the unstable system quickly resume stable operation.