Abstract
In order to improve the accuracy of short-term load forecasting, a hybrid forecasting model based on variational mode decomposition (VMD), fuzzy logic and gated recurrent unit (GRU) is proposed. Firstly, the original load sequence is decomposed into several modal components by VMD algorithm, then the decomposed modal components are combined with the fuzzy processed meteorological information, and then the combined data are inputted into the GRU model for prediction, and finally the prediction results of each modal component are superimposed to obtain the final load prediction results. Through simulation experiments and comparison with other models (SVR, LSTM, GRU, VMD-FGRU), the hybrid model proposed in this paper has better prediction accuracy.
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Acknowledgment
This study was supported by the Key Project of Natural Science Foundation of Jiangxi Province (20224ACB204016).
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Shen, J., Zeng, X., Wang, C., Deng, S., Lin, X. (2024). Research on Short-Term Electric Load Forecasting Based on VMD-FGRU. In: Cai, C., Qu, X., Mai, R., Zhang, P., Chai, W., Wu, S. (eds) The Proceedings of 2023 International Conference on Wireless Power Transfer (ICWPT2023). ICWPT 2023. Lecture Notes in Electrical Engineering, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-97-0877-2_39
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DOI: https://doi.org/10.1007/978-981-97-0877-2_39
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