Consumption–Production Profile Categorization in Energy Communities
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- Voyant, Cyril & Notton, Gilles & Kalogirou, Soteris & Nivet, Marie-Laure & Paoli, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2017. "Machine learning methods for solar radiation forecasting: A review," Renewable Energy, Elsevier, vol. 105(C), pages 569-582.
- Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
- Antonio Bracale & Pierluigi Caramia & Guido Carpinelli & Anna Rita Di Fazio & Gabriella Ferruzzi, 2013. "A Bayesian Method for Short-Term Probabilistic Forecasting of Photovoltaic Generation in Smart Grid Operation and Control," Energies, MDPI, vol. 6(2), pages 1-15, February.
- Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
- María Pérez-Ortiz & Silvia Jiménez-Fernández & Pedro A. Gutiérrez & Enrique Alexandre & César Hervás-Martínez & Sancho Salcedo-Sanz, 2016. "A Review of Classification Problems and Algorithms in Renewable Energy Applications," Energies, MDPI, vol. 9(8), pages 1-27, August.
- Godwin C. Okwuibe & Amin Shokri Gazafroudi & Sarah Hambridge & Christopher Dietrich & Ana Trbovich & Miadreza Shafie-khah & Peter Tzscheutschler & Thomas Hamacher, 2022. "Evaluation of Hierarchical, Multi-Agent, Community-Based, Local Energy Markets Based on Key Performance Indicators," Energies, MDPI, vol. 15(10), pages 1-23, May.
- Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
- Holt, Charles C., 2004. "Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'," International Journal of Forecasting, Elsevier, vol. 20(1), pages 11-13.
- Holt, Charles C., 2004. "Forecasting seasonals and trends by exponentially weighted moving averages," International Journal of Forecasting, Elsevier, vol. 20(1), pages 5-10.
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- Eduardo Gomes & Augusto Esteves & Hugo Morais & Lucas Pereira, 2025. "Leveraging Explainable Artificial Intelligence in Solar Photovoltaic Mappings: Model Explanations and Feature Selection," Energies, MDPI, vol. 18(5), pages 1-17, March.
- Miguel Matos & João Almeida & Pedro Gonçalves & Fabiano Baldo & Fernando José Braz & Paulo C. Bartolomeu, 2024. "A Machine Learning-Based Electricity Consumption Forecast and Management System for Renewable Energy Communities," Energies, MDPI, vol. 17(3), pages 1-25, January.
- Wolfram Rozas-Rodriguez & Rafael Pastor-Vargas & Andrew D. Peacock & David Kane & José Carpio-Ibañez, 2024. "BESS Reserve Optimisation in Energy Communities," Sustainability, MDPI, vol. 16(18), pages 1-18, September.
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Keywords
flexibility; local energy market; predictive sequence models; uncertainty;All these keywords.
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