Multivariate load forecasting of integrated energy system based on GBLA

Pei He, Xiaodong Wang, Yangming Guo

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

There may be complex and strong coupling relationship between various loads in the integrated energy system. Compared with the single and independent forecasting of various loads, the direct development of multivariate load forecasting can further explore the internal relations between loads and improve the forecasting accuracy. This paper presents a prediction model based on GRA-Bi-LSTM-Attention(GBLA). GRA was used to quantitatively analyze the coupling between the influencing factors. Bi-LSTM was used to capture the nonlinear relationship in the multi-load time series and enhance the short-term memory ability. The attention mechanism was introduced to distribute the weight of the prediction results, so as to realize the joint prediction of multi-load. Finally, based on the load data set of typical integrated energy systems, the validation work is carried out, and the comparison analysis is made with other prediction models. The results show that the prediction method proposed in this paper has better performance.

源语言英语
主期刊名2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350357974
DOI
出版状态已出版 - 2023
活动2nd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2023 - Virtual, Online, 美国
期限: 8 12月 202310 12月 2023

出版系列

姓名2023 IEEE 2nd Industrial Electronics Society Annual On-Line Conference, ONCON 2023

会议

会议2nd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2023
国家/地区美国
Virtual, Online
时期8/12/2310/12/23

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