Day-Ahead Wind Power Forecasting in Poland Based on Numerical Weather Prediction
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Cited by:
- Couto, António & Estanqueiro, Ana, 2022. "Enhancing wind power forecast accuracy using the weather research and forecasting numerical model-based features and artificial neuronal networks," Renewable Energy, Elsevier, vol. 201(P1), pages 1076-1085.
- Upma Singh & Mohammad Rizwan & Hasmat Malik & Fausto Pedro García Márquez, 2022. "Wind Energy Scenario, Success and Initiatives towards Renewable Energy in India—A Review," Energies, MDPI, vol. 15(6), pages 1-39, March.
- Michal Pikus & Jarosław Wąs, 2023. "Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship," Energies, MDPI, vol. 16(18), pages 1-15, September.
- Cabello-López, Tomás & Carranza-García, Manuel & Riquelme, José C. & García-Gutiérrez, Jorge, 2023. "Forecasting solar energy production in Spain: A comparison of univariate and multivariate models at the national level," Applied Energy, Elsevier, vol. 350(C).
- Katarzyna Kubiak-Wójcicka & Filip Polak & Leszek Szczęch, 2022. "Water Power Plants Possibilities in Powering Electric Cars—Case Study: Poland," Energies, MDPI, vol. 15(4), pages 1-17, February.
- Manisha Sawant & Rupali Patil & Tanmay Shikhare & Shreyas Nagle & Sakshi Chavan & Shivang Negi & Neeraj Dhanraj Bokde, 2022. "A Selective Review on Recent Advancements in Long, Short and Ultra-Short-Term Wind Power Prediction," Energies, MDPI, vol. 15(21), pages 1-24, October.
- Katarzyna Kubiak-Wójcicka & Leszek Szczęch, 2021. "Dynamics of Electricity Production against the Backdrop of Climate Change: A Case Study of Hydropower Plants in Poland," Energies, MDPI, vol. 14(12), pages 1-24, June.
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Keywords
machine learning; wind power forecasting; day-ahead; numerical weather prediction; ALARO;All these keywords.
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