Reviews on uncertainty analysis of wind power forecasting
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- Zhang, Yao & Wang, Jianxue & Wang, Xifan, 2014. "Review on probabilistic forecasting of wind power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 255-270.
- Wang, J. & Botterud, A. & Bessa, R. & Keko, H. & Carvalho, L. & Issicaba, D. & Sumaili, J. & Miranda, V., 2011. "Wind power forecasting uncertainty and unit commitment," Applied Energy, Elsevier, vol. 88(11), pages 4014-4023.
- Bessa, Ricardo J. & Miranda, V. & Botterud, A. & Zhou, Z. & Wang, J., 2012. "Time-adaptive quantile-copula for wind power probabilistic forecasting," Renewable Energy, Elsevier, vol. 40(1), pages 29-39.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
- Gneiting, Tilmann & Larson, Kristin & Westrick, Kenneth & Genton, Marc G. & Aldrich, Eric, 2006. "Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching SpaceTime Method," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 968-979, September.
- Taylor, James W. & Bunn, Derek W., 1999. "Investigating improvements in the accuracy of prediction intervals for combinations of forecasts: A simulation study," International Journal of Forecasting, Elsevier, vol. 15(3), pages 325-339, July.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
- Yan, Jie & Liu, Yongqian & Han, Shuang & Qiu, Meng, 2013. "Wind power grouping forecasts and its uncertainty analysis using optimized relevance vector machine," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 613-621.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
- Thordis L. Thorarinsdottir & Tilmann Gneiting, 2010. "Probabilistic forecasts of wind speed: ensemble model output statistics by using heteroscedastic censored regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 371-388, April.
- Sanchez, Ismael, 2006. "Short-term prediction of wind energy production," International Journal of Forecasting, Elsevier, vol. 22(1), pages 43-56.
- Costa, Alexandre & Crespo, Antonio & Navarro, Jorge & Lizcano, Gil & Madsen, Henrik & Feitosa, Everaldo, 2008. "A review on the young history of the wind power short-term prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(6), pages 1725-1744, August.
- Pinson, P. & Nielsen, H.Aa. & Madsen, H. & Kariniotakis, G., 2009. "Skill forecasting from ensemble predictions of wind power," Applied Energy, Elsevier, vol. 86(7-8), pages 1326-1334, July.
- Moller, Jan Kloppenborg & Nielsen, Henrik Aalborg & Madsen, Henrik, 2008. "Time-adaptive quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1292-1303, January.
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- Nowotarski, Jakub & Weron, Rafał, 2018.
"Recent advances in electricity price forecasting: A review of probabilistic forecasting,"
Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1548-1568.
- Jakub Nowotarski & Rafal Weron, 2016. "Recent advances in electricity price forecasting: A review of probabilistic forecasting," HSC Research Reports HSC/16/07, Hugo Steinhaus Center, Wroclaw University of Technology.
- Gensler, André & Sick, Bernhard & Vogt, Stephan, 2018. "A review of uncertainty representations and metaverification of uncertainty assessment techniques for renewable energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 352-379.
- Massrur, Hamid Reza & Niknam, Taher & Aghaei, Jamshid & Shafie-khah, Miadreza & Catalão, João P.S., 2018. "A stochastic mid-term scheduling for integrated wind-thermal systems using self-adaptive optimization approach: A comparative study," Energy, Elsevier, vol. 155(C), pages 552-564.
- Park, BeomJun & Hur, Jin, 2018. "Spatial prediction of renewable energy resources for reinforcing and expanding power grids," Energy, Elsevier, vol. 164(C), pages 757-772.
- Wang, Jianzhou & Niu, Tong & Lu, Haiyan & Guo, Zhenhai & Yang, Wendong & Du, Pei, 2018. "An analysis-forecast system for uncertainty modeling of wind speed: A case study of large-scale wind farms," Applied Energy, Elsevier, vol. 211(C), pages 492-512.
- Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, Open Access Journal, vol. 12(11), pages 1-26, June.
- Kim, Deockho & Hur, Jin, 2018. "Short-term probabilistic forecasting of wind energy resources using the enhanced ensemble method," Energy, Elsevier, vol. 157(C), pages 211-226.
- Croonenbroeck, Carsten & Stadtmann, Georg, 2019. "Renewable generation forecast studies – Review and good practice guidance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 312-322.
- Li, Hongmin & Wang, Jianzhou & Lu, Haiyan & Guo, Zhenhai, 2018. "Research and application of a combined model based on variable weight for short term wind speed forecasting," Renewable Energy, Elsevier, vol. 116(PA), pages 669-684.
- Agüera-Pérez, Agustín & Palomares-Salas, José Carlos & González de la Rosa, Juan José & Florencias-Oliveros, Olivia, 2018. "Weather forecasts for microgrid energy management: Review, discussion and recommendations," Applied Energy, Elsevier, vol. 228(C), pages 265-278.
- Paulescu, Marius & Paulescu, Eugenia, 2019. "Short-term forecasting of solar irradiance," Renewable Energy, Elsevier, vol. 143(C), pages 985-994.
- Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
- Fang Liu & Ranran Li & Aliona Dreglea, 2019. "Wind Speed and Power Ultra Short-Term Robust Forecasting Based on Takagi–Sugeno Fuzzy Model," Energies, MDPI, Open Access Journal, vol. 12(18), pages 1-16, September.
- Zhang, Jinhua & Yan, Jie & Infield, David & Liu, Yongqian & Lien, Fue-sang, 2019. "Short-term forecasting and uncertainty analysis of wind turbine power based on long short-term memory network and Gaussian mixture model," Applied Energy, Elsevier, vol. 241(C), pages 229-244.
- Hasan, Kazi Nazmul & Preece, Robin & Milanović, Jovica V., 2019. "Existing approaches and trends in uncertainty modelling and probabilistic stability analysis of power systems with renewable generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 168-180.
- Liu, Hui & Chen, Chao, 2019. "Data processing strategies in wind energy forecasting models and applications: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 392-408.
- Zhang, Kequan & Qu, Zongxi & Dong, Yunxuan & Lu, Haiyan & Leng, Wennan & Wang, Jianzhou & Zhang, Wenyu, 2019. "Research on a combined model based on linear and nonlinear features - A case study of wind speed forecasting," Renewable Energy, Elsevier, vol. 130(C), pages 814-830.
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KeywordsWind power forecasting; Probabilistic forecasting; Interval forecasting; Uncertainty analysis; Impact factors; Classification; Optimization strategy;
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