Title: Power System Transient Stability Control Method Based on Deep Learning Hybrid Model
Abstract: The deep adjustment of power grid structure puts forward new requirements for power system emergency control technology. Aiming at the problem that traditional transient stability control methods only consider power angle stability constraints, resulting in low control accuracy and unable to guarantee the transient voltage stability of power grid, a hybrid model based on deep learning is proposed for power system emergency control. Firstly, the power system emergency control margin model of random forest is established to accurately judge the stability of the system and avoid improper decision-making due to the failure of the model. Secondly, the long short-term memory network is used for real-time power curve prediction to provide accurate implementation scheme of machine and load shedding, so as to realize the stable operation of power system. Finally, simulation analysis is carried out in IEEE 16 machine 68 bus interconnected system. The results show that our method has better system stability judgment accuracy than the comparison method, and the emergency control method can effectively ensure the stable operation of the system after failure.
Publication Year: 2021
Publication Date: 2021-07-18
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 6
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