Wind Speed Forecasting at Different Time Scales Using Time Series and Machine Learning Models
Author:
Publisher
Allerton Press
Subject
Renewable Energy, Sustainability and the Environment
Link
https://link.springer.com/content/pdf/10.3103/S0003701X22601569.pdf
Reference33 articles.
1. Zhou, Q., Wang, C., and Zhang, G., Hybrid forecasting system based on an optimal model selection strategy for different wind speed forecasting problems, Appl. Energy, 2019, vol. 250, pp. 1559–1580.
2. Ministry of New and Renewable Energy, India. https://mnre.gov.in/wind/current-status/. Accessed December, 2022.
3. Singh, A., Gurtej, K., Jain, G., Nayyar, F., and Tripathi, M., Short term wind speed and power forecasting in Indian and UK wind power farms, in 2016 IEEE 7th Power India International Conference (PIICON), 2016, pp. 1–5.
4. Sadullayev, N.N., Safarov, A.B., Nematov, S.N., and Mamedov, R.A., Statistical analysis of wind energy potential in Uzbekistan’s Bukhara region using Weibull distribution, Appl. Sol. Energy, 2019, vol. 55, pp. 126–132.
5. Zakhidov, R.A., Tadjiev, U.A., and Kiseleva, E.I., Prospects for decentralized energy supply to facilities in rural areas using hydraulic, solar, and wind energy, Appl. Sol. Energy, 2018, vol. 55, pp. 384–387.
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