App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 4

Short-term electricity load forecasting using EWT-TOPSIS fusion and volatility-aware attention

Chen Siyi
Hu Shuanglin
Yuan Bo
School of Automation and Electronic Information, Xiangtan University, Xiangtan 411100, China
DOI: 10.19734/j.issn.1001-3695.2025.08.0295

Abstract

Accurate power load forecasting serves as a critical technology for ensuring the safe and stable operation of power grids and optimizing energy dispatch. Addressing the nonlinearity, non-stationarity, and complex temporal variation characteristics of power load sequences, this study proposed a prediction model integrating Empirical Wavelet Transform (EWT) , Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making, and volatility-aware attention mechanism. The model first employed EWT to dynamically decompose load sequences and generate five intrinsic mode functions. It then designed a multi-scale volatility analyzer to extract time-domain statistical features. Subsequently, it constructed a volatility-aware attention mechanism to dynamically modulate sequence weights. Finally, it introduced a two-stage TOPSIS feature fusion layer to achieve optimal integration of multi-source heterogeneous information. Experimental results demonstrate that on the Panama dataset, the model achieves a Mean Absolute Error (MAE) of 39.87MW, Root Mean Squared Error (RMSE) of 57.25MW, and Mean Absolute Percentage Error (MAPE) of 3.21%. Compared to baseline models such as Crossformer and PatchTST, MAE reduces by 10.73%~67.09% and RMSE reduces by 5.81%~61.25%. On the Australian dataset, the model obtains MAE of 191.11MW, RMSE of 244.96MW, and MAPE of 2.06%, with MAE reduction of 2.31%~54.57%. Ablation experiments validate the effectiveness of the frequency-time-statistical feature collaborative modeling and volatility-aware adaptive mechanism.

Foundation Support

湖南省优秀青年科学家基金资助项目(22B0156)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.08.0295
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 4

Publish History

[2025-12-16] Accepted Paper

Cite This Article

陈思溢, 胡双麟, 袁博. 基于EWT-TOPSIS融合和波动性感知注意力的短期电力负荷预测 [J]. 计算机应用研究, 2026, 43 (4). (2025-12-19). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0295. (Chen Siyi, Hu Shuanglin, Yuan Bo. Short-term electricity load forecasting using EWT-TOPSIS fusion and volatility-aware attention [J]. Application Research of Computers, 2026, 43 (4). (2025-12-19). https://doi.org/10.19734/j.issn.1001-3695.2025.08.0295. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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