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Predicting Energy Generation Using Forecasting Techniques in Catalan Reservoirs

Author

Listed:
  • Raúl Parada

    (Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya (UOC), 08035 Barcelona, Spain)

  • Jordi Font

    (Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya (UOC), 08035 Barcelona, Spain)

  • Jordi Casas-Roma

    (Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya (UOC), 08035 Barcelona, Spain)

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 R 2 value of 0.99.

Suggested Citation

  • Raúl Parada & Jordi Font & Jordi Casas-Roma, 2019. "Predicting Energy Generation Using Forecasting Techniques in Catalan Reservoirs," Energies, MDPI, vol. 12(10), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1832-:d:231128
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    References listed on IDEAS

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