Research on genetic algorithm back propagation neural network photovoltaic daily power prediction system

Bo Xiong; Hai Yu; Tianchen Gu; Weiwei Li; Yi Peng; Lidong Guo

doi:10.1117/12.3011540

7 December 2023 Research on genetic algorithm back propagation neural network photovoltaic daily power prediction system

Bo Xiong, Hai Yu, Tianchen Gu, Weiwei Li, Yi Peng, Lidong Guo

Author Affiliations +

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294112 (2023) https://doi.org/10.1117/12.3011540
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

Due to the low prediction accuracy of the existing Back Propagation Neural Network photovoltaic power prediction model, it cannot effectively reflect the intermittency and fluctuation of photovoltaic power range. The photovoltaic prediction system proposed in this paper utilizes the Pauta criterion to identify anomalies in historical input data and uses the genetic algorithm back propagation neural network algorithm for repair and prediction. The method was validated on a 100MW photovoltaic power plant, example analysis shows that genetic algorithm back propagation neural network can effectively improve the accuracy of photovoltaic daily power prediction compared with back propagation neural network.

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

Citation Download Citation

Bo Xiong, Hai Yu, Tianchen Gu, Weiwei Li, Yi Peng, and Lidong Guo "Research on genetic algorithm back propagation neural network photovoltaic daily power prediction system", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294112 (7 December 2023); https://doi.org/10.1117/12.3011540

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