Abstract
Power load forecasting plays a pivotal role in improving the safety and stability of the distribution networks. First, the Prophet and Bi-directional Long short-term memory (BiLSTM) models were established respectively. Then, the CRITIC weight method was used to linearly combine the two models. Finally, the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were defined evaluation indicators. Through comparing with Prophet, BiLSTM, ARIMMA forecasting model of one distribution network, the prediction accuracy of the Prophet-BiLSTM-CRITIC model proposed in this paper was significantly higher than the other single models.
Science-Technology Innovation Platform and Talents Program of Hunan Province, China, under Grant 2019TP1053.
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Li, W., Guo, Q., Wen, M., Zhang, Y., Pan, X., Yang, S. (2022). Energy Internet-Oriented Distribution Network Long-Term Load Forecasting Method Based on Prophet-BiLSTM-CRITIC Mode. In: Hu, C., Cao, W., Zhang, P., Zhang, Z., Tang, X. (eds) Conference Proceedings of 2021 International Joint Conference on Energy, Electrical and Power Engineering. Lecture Notes in Electrical Engineering, vol 899. Springer, Singapore. https://doi.org/10.1007/978-981-19-1922-0_48
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DOI: https://doi.org/10.1007/978-981-19-1922-0_48
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