Modeling research and simulation analysis of large hydro generator based on deep belief network

Jinping Zhao

doi:10.1117/12.2674941

2 May 2023 Modeling research and simulation analysis of large hydro generator based on deep belief network

Jinping Zhao

Proceedings Volume 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023); 1264226 (2023) https://doi.org/10.1117/12.2674941
Event: Second International Conference on Electronic Information Engineering, Big Data and Computer Technology (EIBDCT 2023), 2023, Xishuangbanna, China

Abstract

In view of the problems of complex modeling process, nonlinear and poor multi parameter coupling expression in the mathematical mechanism modeling of hydro generators, and the complex problems of wind and solar energy access and grid interconnection faced by large hydro generators, the advantages and disadvantages of mechanism modeling and data-driven are compared and analyzed, and the feasibility of deep belief network algorithm on hydro generator modeling is studied, A large-scale hydro generator model based on the data-driven method of deep belief network is established. A total of 129600 sets of actual data of a unit are used for model training and verification, and simulation tests are carried out under the no-load frequency disturbance of the unit to verify the effectiveness and stability of the model.

Citation Download Citation

Jinping Zhao "Modeling research and simulation analysis of large hydro generator based on deep belief network", Proc. SPIE 12642, Second International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2023), 1264226 (2 May 2023); https://doi.org/10.1117/12.2674941

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