A Smart Forecasting Approach to District Energy Management
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- Jing, Z.X. & Jiang, X.S. & Wu, Q.H. & Tang, W.H. & Hua, B., 2014. "Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system," Energy, Elsevier, vol. 73(C), pages 399-415.
- Legendre, Bérangère & Ricci, Olivia, 2015.
"Measuring fuel poverty in France: Which households are the most fuel vulnerable?,"
Energy Economics,
Elsevier, vol. 49(C), pages 620-628.
- Bérangère Legendre & Olivia Ricci, 2015. "Measuring fuel poverty in France: Which households are the most fuel vulnerable?," Post-Print hal-01283999, HAL.
- Bérangère Legendre & Olivia Ricci, 2015. "Measuring fuel poverty in France: Which households are the most fuel vulnerable?," Post-Print hal-01245305, HAL.
- Powell, Kody M. & Sriprasad, Akshay & Cole, Wesley J. & Edgar, Thomas F., 2014. "Heating, cooling, and electrical load forecasting for a large-scale district energy system," Energy, Elsevier, vol. 74(C), pages 877-885.
- Hernández, Luis & Baladrón, Carlos & Aguiar, Javier M. & Carro, Belén & Sánchez-Esguevillas, Antonio & Lloret, Jaime, 2014. "Artificial neural networks for short-term load forecasting in microgrids environment," Energy, Elsevier, vol. 75(C), pages 252-264.
- Pearson, Peter J.G. & Foxon, Timothy J., 2012. "A low carbon industrial revolution? Insights and challenges from past technological and economic transformations," Energy Policy, Elsevier, vol. 50(C), pages 117-127.
- Jason Grant & Moataz Eltoukhy & Shihab Asfour, 2014. "Short-Term Electrical Peak Demand Forecasting in a Large Government Building Using Artificial Neural Networks," Energies, MDPI, vol. 7(4), pages 1-19, March.
- Karin Kandananond, 2011. "Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach," Energies, MDPI, vol. 4(8), pages 1-12, August.
- Luis Hernández & Carlos Baladrón & Javier M. Aguiar & Lorena Calavia & Belén Carro & Antonio Sánchez-Esguevillas & Francisco Pérez & Ángel Fernández & Jaime Lloret, 2014. "Artificial Neural Network for Short-Term Load Forecasting in Distribution Systems," Energies, MDPI, vol. 7(3), pages 1-23, March.
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Cited by:
- Agüera-Pérez, Agustín & Palomares-Salas, José Carlos & González de la Rosa, Juan José & Florencias-Oliveros, Olivia, 2018. "Weather forecasts for microgrid energy management: Review, discussion and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 265-278.
- Jason Runge & Radu Zmeureanu, 2021. "A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings," Energies, MDPI, vol. 14(3), pages 1-26, January.
- Davut Solyali, 2020. "A Comparative Analysis of Machine Learning Approaches for Short-/Long-Term Electricity Load Forecasting in Cyprus," Sustainability, MDPI, vol. 12(9), pages 1-34, April.
- Roman V. Klyuev & Irbek D. Morgoev & Angelika D. Morgoeva & Oksana A. Gavrina & Nikita V. Martyushev & Egor A. Efremenkov & Qi Mengxu, 2022. "Methods of Forecasting Electric Energy Consumption: A Literature Review," Energies, MDPI, vol. 15(23), pages 1-33, November.
- Jessica Hermanns & Marcel Modemann & Kamil Korotkiewicz & Frederik Paulat & Kevin Kotthaus & Sven Pack & Markus Zdrallek, 2020. "Evaluation of Different Development Possibilities of Distribution Grid State Forecasts," Energies, MDPI, vol. 13(8), pages 1-17, April.
- Sébastien Bissey & Sébastien Jacques & Jean-Charles Le Bunetel, 2017. "The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing," Energies, MDPI, vol. 10(11), pages 1-24, October.
- Eva Lucas Segarra & Hu Du & Germán Ramos Ruiz & Carlos Fernández Bandera, 2019. "Methodology for the Quantification of the Impact of Weather Forecasts in Predictive Simulation Models," Energies, MDPI, vol. 12(7), pages 1-16, April.
- Zheng, Zhuang & Shafique, Muhammad & Luo, Xiaowei & Wang, Shengwei, 2024. "A systematic review towards integrative energy management of smart grids and urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
- Jason Runge & Radu Zmeureanu, 2019. "Forecasting Energy Use in Buildings Using Artificial Neural Networks: A Review," Energies, MDPI, vol. 12(17), pages 1-27, August.
- Sarah Hadri & Mehdi Najib & Mohamed Bakhouya & Youssef Fakhri & Mohamed El Arroussi, 2021. "Performance Evaluation of Forecasting Strategies for Electricity Consumption in Buildings," Energies, MDPI, vol. 14(18), pages 1-17, September.
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Keywords
ANN; PCA; MRA; district energy management; smart grid; smart cities; demand forecasting;All these keywords.
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