Multimode hydropower power prediction based on long short-term memory

Yijie Zou; Hongkun Chen; Yifan Zhang; Zihao Wang; Ling Pang; Xingchen Lan; Yitong Zhao; Tao Liu; Bo Wang; Ran Peng

doi:10.1117/12.3004172

11 October 2023 Multimode hydropower power prediction based on long short-term memory

Yijie Zou, Hongkun Chen, Yifan Zhang, Zihao Wang, Ling Pang, Xingchen Lan, Yitong Zhao, Tao Liu, Bo Wang, Ran Peng

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128003O (2023) https://doi.org/10.1117/12.3004172
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

In order to improve the accuracy of hydropower forecast, a new power generation prediction method combining empirical mode decomposition (EMD), principal component analysis (PCA), sparrow search algorithm (SSA) and long and short term memory (LSTM) network model was proposed. Firstly, the original generated sequence was decomposed into multiple sequence components by adaptive noise global empirical mode decomposition to reduce the random fluctuation of the generated sequence. Then principal component analysis was used to extract the key influencing factors of feature sequences to eliminate the correlation and redundancy of original sequences. Finally, a linear LSTM model was constructed for each component, and the prediction results of the two models were combined and weighted to obtain the prediction results of each component. Aiming at the optimization problem of important parameters in the LSTM model, Sparrow search algorithm (SSA) is introduced to optimize the model parameters, sum and reconstruct the prediction results of each component, and get the final power prediction results. Taking the measured data of a hydropower station in Sichuan as an example, the experimental results show that the method is effective.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yijie Zou, Hongkun Chen, Yifan Zhang, Zihao Wang, Ling Pang, Xingchen Lan, Yitong Zhao, Tao Liu, Bo Wang, and Ran Peng "Multimode hydropower power prediction based on long short-term memory", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128003O (11 October 2023); https://doi.org/10.1117/12.3004172

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