Forecast of Community Total Electric Load and HVAC Component Disaggregation through a New LSTM-Based Method
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- Bidong Liu & Jakub Nowotarski & Tao Hong & Rafal Weron, 2015. "Probabilistic load forecasting via Quantile Regression Averaging on sister forecasts," HSC Research Reports HSC/15/01, Hugo Steinhaus Center, Wroclaw University of Technology.
- Hong, Tao & Pinson, Pierre & Fan, Shu & Zareipour, Hamidreza & Troccoli, Alberto & Hyndman, Rob J., 2016. "Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond," International Journal of Forecasting, Elsevier, vol. 32(3), pages 896-913.
- Mingzhe Zou & Shuyang Zhu & Jiacheng Gu & Lidija M. Korunovic & Sasa Z. Djokic, 2021. "Heating and Lighting Load Disaggregation Using Frequency Components and Convolutional Bidirectional Long Short-Term Memory Method," Energies, MDPI, vol. 14(16), pages 1-24, August.
- Nick MacMackin, & Miller, Lindsay & Carriveau, Rupp, 2019. "Modeling and disaggregating hourly effects of weather on sectoral electricity demand," Energy, Elsevier, vol. 188(C).
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Cited by:
- Massidda, Luca & Marrocu, Marino, 2023. "Total and thermal load forecasting in residential communities through probabilistic methods and causal machine learning," Applied Energy, Elsevier, vol. 351(C).
- Evan S. Jones & Rosemary E. Alden & Huangjie Gong & Dan M. Ionel, 2023. "Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
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Keywords
distribution power system; smart grid; electric load forecasting; community power; baseload; HVAC system power; disaggregation; air-conditioning; heating; NILM; smart meter; big data; machine learning; LSTM;All these keywords.
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