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Title: Predicting energy generation using forecasting techniques in Catalan reservoirs
Author: Parada Medina, Raúl  
Font Marcé, Jordi  
Casas-Roma, Jordi  
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Citation: Parada Medina, R., Font, J. & Casas-Roma, J. (2019). Predicting energy generation using forecasting techniques in Catalan reservoirs. Energies, 12(10), 1-21. doi: 10.3390/en12101832
Abstract: Reservoirs are natural or artificial lakes used as a source of water supply for society daily applications. In addition, hydroelectric power plants produce electricity while water flows through the reservoir. However, reservoirs are limited natural resources since water levels vary according to annual rainfalls and other natural events, and consequently, the energy generation. Therefore, forecasting techniques are helpful to predict water level, and thus, electricity production. This paper examines state-of-the-art methods to predict the water level in Catalan reservoirs comparing two approaches: using the water level uniquely, uni-variant; and adding meteorological data, multi-variant. With respect to relating works, our contribution includes a longer times series prediction keeping a high precision. The results return that combining Support Vector Machine and the multi-variant approach provides the highest precision with an R2 value of 0.99.
Keywords: Forecasting
Series analysis
DOI: 10.3390/en12101832
Document type: info:eu-repo/semantics/article
Version: info:eu-repo/semantics/publishedVersion
Issue Date: 14-May-2019
Publication license:  
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