Exploring the PV Power Forecasting at Building Façades Using Gradient Boosting Methods
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- Jesús Polo & Nuria Martín-Chivelet & Carlos Sanz-Saiz, 2022. "BIPV Modeling with Artificial Neural Networks: Towards a BIPV Digital Twin," Energies, MDPI, vol. 15(11), pages 1-11, June.
- Nuria Martín-Chivelet & Jesús Polo & Carlos Sanz-Saiz & Lucy Tamara Núñez Benítez & Miguel Alonso-Abella & José Cuenca, 2022. "Assessment of PV Module Temperature Models for Building-Integrated Photovoltaics (BIPV)," Sustainability, MDPI, vol. 14(3), pages 1-15, January.
- Federico Divina & Miguel García Torres & Francisco A. Goméz Vela & José Luis Vázquez Noguera, 2019. "A Comparative Study of Time Series Forecasting Methods for Short Term Electric Energy Consumption Prediction in Smart Buildings," Energies, MDPI, vol. 12(10), pages 1-23, May.
- Walker, Linus & Hofer, Johannes & Schlueter, Arno, 2019. "High-resolution, parametric BIPV and electrical systems modeling and design," Applied Energy, Elsevier, vol. 238(C), pages 164-179.
- Qing, Xiangyun & Niu, Yugang, 2018. "Hourly day-ahead solar irradiance prediction using weather forecasts by LSTM," Energy, Elsevier, vol. 148(C), pages 461-468.
- Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Yadav, Somil & Panda, S.K. & Hachem-Vermette, Caroline, 2020. "Optimum azimuth and inclination angle of BIPV panel owing to different factors influencing the shadow of adjacent building," Renewable Energy, Elsevier, vol. 162(C), pages 381-396.
- Liu, Da & Sun, Kun, 2019. "Random forest solar power forecast based on classification optimization," Energy, Elsevier, vol. 187(C).
- Sharadga, Hussein & Hajimirza, Shima & Balog, Robert S., 2020. "Time series forecasting of solar power generation for large-scale photovoltaic plants," Renewable Energy, Elsevier, vol. 150(C), pages 797-807.
- Saoud A. Al-Janahi & Omar Ellabban & Sami G. Al-Ghamdi, 2020. "A Novel BIPV Reconfiguration Algorithm for Maximum Power Generation under Partial Shading," Energies, MDPI, vol. 13(17), pages 1-25, August.
- Martina Pelle & Elena Lucchi & Laura Maturi & Alexander Astigarraga & Francesco Causone, 2020. "Coloured BIPV Technologies: Methodological and Experimental Assessment for Architecturally Sensitive Areas," Energies, MDPI, vol. 13(17), pages 1-21, September.
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- Domenico Palladino & Nicolandrea Calabrese, 2023. "Energy Planning of Renewable Energy Sources in an Italian Context: Energy Forecasting Analysis of Photovoltaic Systems in the Residential Sector," Energies, MDPI, vol. 16(7), pages 1-28, March.
- Fouzi Harrou & Ying Sun & Bilal Taghezouit & Abdelkader Dairi, 2023. "Artificial Intelligence Techniques for Solar Irradiance and PV Modeling and Forecasting," Energies, MDPI, vol. 16(18), pages 1-5, September.
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Keywords
BIPV; PV power forecasting; machine learning; gradient boosting algorithms;All these keywords.
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