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The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece

Author

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  • Evangelos Spiliotis

    (Forecasting and Strategy Unit, School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
    These authors contributed equally to this work.)

  • Fotios Petropoulos

    (School of Management, University of Bath, Bath BA2 7AY, UK
    These authors contributed equally to this work.)

  • Konstantinos Nikolopoulos

    (ForLAB, Bangor Business School, Bangor University, Bangor LL57 2DG, UK
    These authors contributed equally to this work.)

Abstract

Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical and machine learning) for the case of wind power generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% prediction intervals. The results indicate that different methods should be considered according to the uncertainty characterizing the weather forecasts.

Suggested Citation

  • Evangelos Spiliotis & Fotios Petropoulos & Konstantinos Nikolopoulos, 2020. "The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece," Energies, MDPI, vol. 13(8), pages 1-18, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1880-:d:344678
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    References listed on IDEAS

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    1. Adam Krechowicz & Maria Krechowicz & Katarzyna Poczeta, 2022. "Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources," Energies, MDPI, vol. 15(23), pages 1-41, December.
    2. Paweł Piotrowski & Marcin Kopyt & Dariusz Baczyński & Sylwester Robak & Tomasz Gulczyński, 2021. "Hybrid and Ensemble Methods of Two Days Ahead Forecasts of Electric Energy Production in a Small Wind Turbine," Energies, MDPI, vol. 14(5), pages 1-25, February.

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