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Comparison of numerical weather prediction based deterministic and probabilistic wind resource assessment methods

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  1. Xuejiao Ma & Dandan Liu, 2016. "Comparative Study of Hybrid Models Based on a Series of Optimization Algorithms and Their Application in Energy System Forecasting," Energies, MDPI, vol. 9(8), pages 1-34, August.
  2. Belqasem Aljafari & Subramanian Vasantharaj & Vairavasundaram Indragandhi & Rhanganath Vaibhav, 2022. "Optimization of DC, AC, and Hybrid AC/DC Microgrid-Based IoT Systems: A Review," Energies, MDPI, vol. 15(18), pages 1-30, September.
  3. Yuxuan Shi & Yanyu Wang & Haoran Zheng, 2022. "Wind Speed Prediction for Offshore Sites Using a Clockwork Recurrent Network," Energies, MDPI, vol. 15(3), pages 1-18, January.
  4. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
  5. Allen, D.J. & Tomlin, A.S. & Bale, C.S.E. & Skea, A. & Vosper, S. & Gallani, M.L., 2017. "A boundary layer scaling technique for estimating near-surface wind energy using numerical weather prediction and wind map data," Applied Energy, Elsevier, vol. 208(C), pages 1246-1257.
  6. Zhang, Zhendong & Dai, Huichao & Jiang, Dingguo & Yu, Yi & Tian, Rui, 2024. "Multi-step ahead forecasting of wind vector for multiple wind turbines based on new deep learning model," Energy, Elsevier, vol. 304(C).
  7. Zhao, Yongning & Ye, Lin & Li, Zhi & Song, Xuri & Lang, Yansheng & Su, Jian, 2016. "A novel bidirectional mechanism based on time series model for wind power forecasting," Applied Energy, Elsevier, vol. 177(C), pages 793-803.
  8. Sun, Mucun & Feng, Cong & Zhang, Jie, 2020. "Probabilistic solar power forecasting based on weather scenario generation," Applied Energy, Elsevier, vol. 266(C).
  9. Fu, Wenlong & Zhang, Kai & Wang, Kai & Wen, Bin & Fang, Ping & Zou, Feng, 2021. "A hybrid approach for multi-step wind speed forecasting based on two-layer decomposition, improved hybrid DE-HHO optimization and KELM," Renewable Energy, Elsevier, vol. 164(C), pages 211-229.
  10. Yang, Dongchuan & Li, Mingzhu & Guo, Ju-e & Du, Pei, 2024. "An attention-based multi-input LSTM with sliding window-based two-stage decomposition for wind speed forecasting," Applied Energy, Elsevier, vol. 375(C).
  11. Zhang, Guangchao & Zheng, Xiaoxiao & Liu, Shi & Chen, Minxin, 2022. "Three-dimensional wind field reconstruction using tucker decomposition with optimal sensor placement," Energy, Elsevier, vol. 260(C).
  12. Li, Ranran & Jin, Yu, 2018. "A wind speed interval prediction system based on multi-objective optimization for machine learning method," Applied Energy, Elsevier, vol. 228(C), pages 2207-2220.
  13. Muhammad Shahzad Nazir & Fahad Alturise & Sami Alshmrany & Hafiz. M. J Nazir & Muhammad Bilal & Ahmad N. Abdalla & P. Sanjeevikumar & Ziad M. Ali, 2020. "Wind Generation Forecasting Methods and Proliferation of Artificial Neural Network: A Review of Five Years Research Trend," Sustainability, MDPI, vol. 12(9), pages 1-27, May.
  14. Wu, Chunlei & Luo, Kun & Wang, Qiang & Fan, Jianren, 2022. "A refined wind farm parameterization for the weather research and forecasting model," Applied Energy, Elsevier, vol. 306(PB).
  15. Guangchao Zhang & Shi Liu, 2023. "Reconstruction of Unsteady Wind Field Based on CFD and Reduced-Order Model," Mathematics, MDPI, vol. 11(10), pages 1-25, May.
  16. Wenlong Fu & Kai Wang & Jianzhong Zhou & Yanhe Xu & Jiawen Tan & Tie Chen, 2019. "A Hybrid Approach for Multi-Step Wind Speed Forecasting Based on Multi-Scale Dominant Ingredient Chaotic Analysis, KELM and Synchronous Optimization Strategy," Sustainability, MDPI, vol. 11(6), pages 1-24, March.
  17. Liu, Zhenkun & Jiang, Ping & Zhang, Lifang & Niu, Xinsong, 2020. "A combined forecasting model for time series: Application to short-term wind speed forecasting," Applied Energy, Elsevier, vol. 259(C).
  18. Aliashim Albani & Mohd Zamri Ibrahim, 2017. "Wind Energy Potential and Power Law Indexes Assessment for Selected Near-Coastal Sites in Malaysia," Energies, MDPI, vol. 10(3), pages 1-21, March.
  19. Aliashim Albani & Mohd Zamri Ibrahim & Kim Hwang Yong, 2018. "Influence of the ENSO and Monsoonal Season on Long-Term Wind Energy Potential in Malaysia," Energies, MDPI, vol. 11(11), pages 1-18, November.
  20. Dylan Harrison-Atlas & Galen Maclaurin & Eric Lantz, 2021. "Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential," Energies, MDPI, vol. 14(12), pages 1-28, June.
  21. Zhang, Wenyu & Zhang, Lifang & Wang, Jianzhou & Niu, Xinsong, 2020. "Hybrid system based on a multi-objective optimization and kernel approximation for multi-scale wind speed forecasting," Applied Energy, Elsevier, vol. 277(C).
  22. Wu, Chunlei & Luo, Kun & Wang, Qiang & Fan, Jianren, 2022. "Simulated potential wind power sensitivity to the planetary boundary layer parameterizations combined with various topography datasets in the weather research and forecasting model," Energy, Elsevier, vol. 239(PB).
  23. Yang, Xiaolei & Milliren, Christopher & Kistner, Matt & Hogg, Christopher & Marr, Jeff & Shen, Lian & Sotiropoulos, Fotis, 2021. "High-fidelity simulations and field measurements for characterizing wind fields in a utility-scale wind farm," Applied Energy, Elsevier, vol. 281(C).
  24. Wang, Jianzhou & Yang, Wendong & Du, Pei & Li, Yifan, 2018. "Research and application of a hybrid forecasting framework based on multi-objective optimization for electrical power system," Energy, Elsevier, vol. 148(C), pages 59-78.
  25. Wenqi Zhang & William Kleiber & Bri‐Mathias Hodge & Barry Mather, 2022. "A nonstationary and non‐Gaussian moving average model for solar irradiance," Environmetrics, John Wiley & Sons, Ltd., vol. 33(3), May.
  26. Sun, Mucun & Feng, Cong & Zhang, Jie, 2019. "Conditional aggregated probabilistic wind power forecasting based on spatio-temporal correlation," Applied Energy, Elsevier, vol. 256(C).
  27. Sun, Mucun & Feng, Cong & Chartan, Erol Kevin & Hodge, Bri-Mathias & Zhang, Jie, 2019. "A two-step short-term probabilistic wind forecasting methodology based on predictive distribution optimization," Applied Energy, Elsevier, vol. 238(C), pages 1497-1505.
  28. Zhang, Zhendong & Ye, Lei & Qin, Hui & Liu, Yongqi & Wang, Chao & Yu, Xiang & Yin, Xingli & Li, Jie, 2019. "Wind speed prediction method using Shared Weight Long Short-Term Memory Network and Gaussian Process Regression," Applied Energy, Elsevier, vol. 247(C), pages 270-284.
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