An integrated energy system scheduling method based on SSA-BI-GRU multivariate load forecasting

Xueying Zhuge; Zesan Liu; Hongmin Meng; Guangyang Zhou; Zhenan Xu; Shu Huang; Yurong Yan

doi:10.1117/12.3024559

13 May 2024 An integrated energy system scheduling method based on SSA-BI-GRU multivariate load forecasting

Xueying Zhuge, Zesan Liu, Hongmin Meng, Guangyang Zhou, Zhenan Xu, Shu Huang, Yurong Yan

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 131591T (2024) https://doi.org/10.1117/12.3024559
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

The multiple loads of the integrated energy system have the characteristics of complex coupling, strong volatility, and strong randomness, and accurate prediction is the foundation and guarantee for optimizing the scheduling of the integrated energy system. An integrated energy system scheduling method based on SSA-BI-GRU multivariate load forecasting is proposed. Firstly, in order to explore the relationships between data more fully, the SSA-BI-GRU algorithm is proposed. Random forest regression model and cross-telecommunication validation are introduced into the data processing module. Then, we construct an integrated energy system optimization scheduling model to incorporate system reliability into the objective function. Finally, the load prediction results of the SSA-BI-GRU model are used as input to solve the IES scheduling problem using the improved MOGWO algorithm. The results show that SSA-BI-GRU improves the accuracy and speed of load forecasting, and the established multi-energy flow coupling optimization scheduling model achieves the economic, efficient, and reliable operation of IES.

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

Citation Download Citation

Xueying Zhuge, Zesan Liu, Hongmin Meng, Guangyang Zhou, Zhenan Xu, Shu Huang, and Yurong Yan "An integrated energy system scheduling method based on SSA-BI-GRU multivariate load forecasting", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 131591T (13 May 2024); https://doi.org/10.1117/12.3024559

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