Accurate forecasting method of new energy power in multi-temporal and spatial scales by CNN-BiLSTM

Zhengdeng Ye; Jing Chen; Run Li; Zhekai Tu; Peng Wu; Qibo Yan

doi:10.1117/12.3034059

16 October 2024 Accurate forecasting method of new energy power in multi-temporal and spatial scales by CNN-BiLSTM

Zhengdeng Ye, Jing Chen, Run Li, Zhekai Tu, Peng Wu, Qibo Yan

Author Affiliations +

Proceedings Volume 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024); 132916R (2024) https://doi.org/10.1117/12.3034059
Event: Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 2024, Changchun, China

Abstract

To address the issue of disregarding weather factors in the current prediction process for new energy power, which leads to inaccurate predictions for new energy power stations, a novel approach is proposed. This method utilizes a combination of CNN-BiLSTM models to achieve accurate predictions across multiple time and spatial scales. According to the known data, the data gaps are filled, and the interval average of time series is calculated. On this basis, the data of multi-time and space scale accurate prediction of new energy power are normalized. Combining CNN and BiLSTM, the specific steps of accurate prediction of new energy power in multiple time and space scales are designed. The experimental findings demonstrate that this approach exhibits excellent predictive performance, outperforming other methods in terms of two evaluation metrics: mean square error and average absolute error rate for the accurate forecasting of new energy power across multiple time scales.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhengdeng Ye, Jing Chen, Run Li, Zhekai Tu, Peng Wu, and Qibo Yan "Accurate forecasting method of new energy power in multi-temporal and spatial scales by CNN-BiLSTM", Proc. SPIE 13291, Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), 132916R (16 October 2024); https://doi.org/10.1117/12.3034059

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