Abstract
Once energy is a social good, this study proposes a methodology to select the most appropriate wind turbine power curve models for Brazilian wind farms. To do so, we compare our proposal with the observed values in a monthly and annual base.
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Acknowledgements
The authors thank the R&D program of the Brazilian Electricity Regulatory Agency (ANEEL) for financial support (PD-0387-0315/2015). They also thank the support of the National Council of Technological and Scientific Development (CNPq) and FAPERJ. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES)—Finance Code 001.
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Hammes, G.A., Maçaira, P.M., Cyrino Oliveira, F.L. (2020). Data Analytics for the Selection of Wind Turbine Power Curve Models. In: Leiras, A., González-Calderón, C., de Brito Junior, I., Villa, S., Yoshizaki, H. (eds) Operations Management for Social Good. POMS 2018. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-23816-2_4
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