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Electrical load-temperature CNN for residential load forecasting

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  1. Zhang, Yagang & Wang, Hui & Wang, Jingchao & Cheng, Xiaodan & Wang, Tong & Zhao, Zheng, 2024. "Ensemble optimization approach based on hybrid mode decomposition and intelligent technology for wind power prediction system," Energy, Elsevier, vol. 292(C).
  2. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.
  3. Corcoran, Lloyd & Saikia, Pranaynil & Ugalde-Loo, Carlos E. & Abeysekera, Muditha, 2025. "An effective methodology to quantify cooling demand in the UK housing stock," Applied Energy, Elsevier, vol. 380(C).
  4. Sekhar, Charan & Dahiya, Ratna, 2023. "Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand," Energy, Elsevier, vol. 268(C).
  5. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  6. Gao, Hongchao & Jin, Tai & Feng, Cheng & Li, Chuyi & Chen, Qixin & Kang, Chongqing, 2024. "Review of virtual power plant operations: Resource coordination and multidimensional interaction," Applied Energy, Elsevier, vol. 357(C).
  7. Huang, Yanmei & Hasan, Najmul & Deng, Changrui & Bao, Yukun, 2022. "Multivariate empirical mode decomposition based hybrid model for day-ahead peak load forecasting," Energy, Elsevier, vol. 239(PC).
  8. Jiakang Wang & Hui Liu & Guangji Zheng & Ye Li & Shi Yin, 2023. "Short-Term Load Forecasting Based on Outlier Correction, Decomposition, and Ensemble Reinforcement Learning," Energies, MDPI, vol. 16(11), pages 1-16, May.
  9. Lu, Shixiang & Xu, Qifa & Jiang, Cuixia & Liu, Yezheng & Kusiak, Andrew, 2022. "Probabilistic load forecasting with a non-crossing sparse-group Lasso-quantile regression deep neural network," Energy, Elsevier, vol. 242(C).
  10. Hu, Zehuan & Gao, Yuan & Sun, Luning & Mae, Masayuki & Imaizumi, Taiji, 2024. "Self-learning dynamic graph neural network with self-attention based on historical data and future data for multi-task multivariate residential air conditioning forecasting," Applied Energy, Elsevier, vol. 364(C).
  11. Han Qiu & Rong Hu & Jiaqing Chen & Zihao Yuan, 2025. "Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Network–Bidirectional Lon," Mathematics, MDPI, vol. 13(5), pages 1-32, February.
  12. Alfredo Candela Esclapez & Miguel López García & Sergio Valero Verdú & Carolina Senabre Blanes, 2022. "Automatic Selection of Temperature Variables for Short-Term Load Forecasting," Sustainability, MDPI, vol. 14(20), pages 1-22, October.
  13. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  14. Filipe Rodrigues & Carlos Cardeira & João M. F. Calado & Rui Melicio, 2023. "Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review," Energies, MDPI, vol. 16(10), pages 1-26, May.
  15. Zheyu He & Rongheng Lin & Budan Wu & Xin Zhao & Hua Zou, 2023. "Pre-Attention Mechanism and Convolutional Neural Network Based Multivariate Load Prediction for Demand Response," Energies, MDPI, vol. 16(8), pages 1-13, April.
  16. Zhi Rao & Zaimin Yang & Xiongping Yang & Jiaming Li & Wenchuan Meng & Zhichu Wei, 2024. "TCN-GRU Based on Attention Mechanism for Solar Irradiance Prediction," Energies, MDPI, vol. 17(22), pages 1-17, November.
  17. Wu, Jiahui & Wang, Jidong & Kong, Xiangyu, 2022. "Strategic bidding in a competitive electricity market: An intelligent method using Multi-Agent Transfer Learning based on reinforcement learning," Energy, Elsevier, vol. 256(C).
  18. Yijun Wang & Peiqian Guo & Nan Ma & Guowei Liu, 2022. "Robust Wavelet Transform Neural-Network-Based Short-Term Load Forecasting for Power Distribution Networks," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
  19. Yeeun Moon & Younjeong Lee & Yejin Hwang & Jongpil Jeong, 2024. "Long Short-Term Memory Autoencoder and Extreme Gradient Boosting-Based Factory Energy Management Framework for Power Consumption Forecasting," Energies, MDPI, vol. 17(15), pages 1-21, July.
  20. Mingping Liu & Xihao Sun & Qingnian Wang & Suhui Deng, 2022. "Short-Term Load Forecasting Using EMD with Feature Selection and TCN-Based Deep Learning Model," Energies, MDPI, vol. 15(19), pages 1-22, September.
  21. Fazlipour, Zahra & Mashhour, Elaheh & Joorabian, Mahmood, 2022. "A deep model for short-term load forecasting applying a stacked autoencoder based on LSTM supported by a multi-stage attention mechanism," Applied Energy, Elsevier, vol. 327(C).
  22. Ruixiang Zhang & Ziyu Zhu & Meng Yuan & Yihan Guo & Jie Song & Xuanxuan Shi & Yu Wang & Yaojie Sun, 2023. "Regional Residential Short-Term Load-Interval Forecasting Based on SSA-LSTM and Load Consumption Consistency Analysis," Energies, MDPI, vol. 16(24), pages 1-17, December.
  23. Luo, Jie & Wen, Chao & Peng, Qiyuan & Qin, Yong & Huang, Ping, 2023. "Forecasting the effect of traffic control strategies in railway systems: A hybrid machine learning method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).
  24. Zhang, Bidan & He, Guannan & Du, Yang & Wen, Haoran & Huan, Xintao & Xing, Bowen & Huang, Jingsi, 2024. "Assessment of the economic impact of forecasting errors in Peer-to-Peer energy trading," Applied Energy, Elsevier, vol. 374(C).
  25. Shi, Jiaqi & Li, Chenxi & Yan, Xiaohe, 2023. "Artificial intelligence for load forecasting: A stacking learning approach based on ensemble diversity regularization," Energy, Elsevier, vol. 262(PB).
  26. Yin, Chen & Mao, Shuhua, 2023. "Fractional multivariate grey Bernoulli model combined with improved grey wolf algorithm: Application in short-term power load forecasting," Energy, Elsevier, vol. 269(C).
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