Abstract
The increasing penetration of renewable energy sources and the need to adjust to the future demand requires adopting measures to improve energy resources management, especially in buildings. In this context, PV generation forecast has an essential role in the energy management entities by preventing problems related to intermittent weather conditions and allowing participation in incentive programs to reduce energy consumption. This paper proposes an automatic model for the day-ahead PV generation forecast, combining several forecasting algorithms with the expected weather conditions. To this end, this model communicates with a SCADA system, which is responsible for the cyber-physical energy management of an actual building.
This work was supported by the MAS-Society Project co-funded by Portugal 2020 Fundo Europeu de Desenvolvimento Regional (FEDER) through PO CI, and under Grant UIDB/00760/2020. Brígida Teixeira was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) PhD studentship with reference 2020.08174.BD.
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References
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Teixeira, B., Pinto, T., Faria, P., Vale, Z. (2021). PV Generation Forecasting Model for Energy Management in Buildings. In: Marreiros, G., Melo, F.S., Lau, N., Lopes Cardoso, H., Reis, L.P. (eds) Progress in Artificial Intelligence. EPIA 2021. Lecture Notes in Computer Science(), vol 12981. Springer, Cham. https://doi.org/10.1007/978-3-030-86230-5_14
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DOI: https://doi.org/10.1007/978-3-030-86230-5_14
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