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A novel approach for the forecasting of mean hourly wind speed time series

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Cited by:

  1. Bentsen, Lars Ødegaard & Warakagoda, Narada Dilp & Stenbro, Roy & Engelstad, Paal, 2023. "Spatio-temporal wind speed forecasting using graph networks and novel Transformer architectures," Applied Energy, Elsevier, vol. 333(C).
  2. I A Eckley & G P Nason, 2018. "A test for the absence of aliasing or local white noise in locally stationary wavelet time series," Biometrika, Biometrika Trust, vol. 105(4), pages 833-848.
  3. Alonzo, Bastien & Ringkjob, Hans-Kristian & Jourdier, Benedicte & Drobinski, Philippe & Plougonven, Riwal & Tankov, Peter, 2017. "Modelling the variability of the wind energy resource on monthly and seasonal timescales," Renewable Energy, Elsevier, vol. 113(C), pages 1434-1446.
  4. Liu, Hui & Chen, Chao & Tian, Hong-qi & Li, Yan-fei, 2012. "A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks," Renewable Energy, Elsevier, vol. 48(C), pages 545-556.
  5. Peng, Xiaosheng & Wang, Hongyu & Lang, Jianxun & Li, Wenze & Xu, Qiyou & Zhang, Zuowei & Cai, Tao & Duan, Shanxu & Liu, Fangjie & Li, Chaoshun, 2021. "EALSTM-QR: Interval wind-power prediction model based on numerical weather prediction and deep learning," Energy, Elsevier, vol. 220(C).
  6. A. Alexandridis & A. Zapranis, 2013. "Wind Derivatives: Modeling and Pricing," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 299-326, March.
  7. Jiani Heng & Chen Wang & Xuejing Zhao & Liye Xiao, 2016. "Research and Application Based on Adaptive Boosting Strategy and Modified CGFPA Algorithm: A Case Study for Wind Speed Forecasting," Sustainability, MDPI, vol. 8(3), pages 1-25, March.
  8. Lahouar, A. & Ben Hadj Slama, J., 2017. "Hour-ahead wind power forecast based on random forests," Renewable Energy, Elsevier, vol. 109(C), pages 529-541.
  9. Lei, Ma & Shiyan, Luan & Chuanwen, Jiang & Hongling, Liu & Yan, Zhang, 2009. "A review on the forecasting of wind speed and generated power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 915-920, May.
  10. Salcedo-Sanz, Sancho & Ángel M. Pérez-Bellido, & Ortiz-García, Emilio G. & Portilla-Figueras, Antonio & Prieto, Luis & Paredes, Daniel, 2009. "Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction," Renewable Energy, Elsevier, vol. 34(6), pages 1451-1457.
  11. Ramirez-Rosado, Ignacio J. & Fernandez-Jimenez, L. Alfredo & Monteiro, Cláudio & Sousa, João & Bessa, Ricardo, 2009. "Comparison of two new short-term wind-power forecasting systems," Renewable Energy, Elsevier, vol. 34(7), pages 1848-1854.
  12. Ata, Rasit, 2015. "Artificial neural networks applications in wind energy systems: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 534-562.
  13. Philippopoulos, Kostas & Deligiorgi, Despina, 2012. "Application of artificial neural networks for the spatial estimation of wind speed in a coastal region with complex topography," Renewable Energy, Elsevier, vol. 38(1), pages 75-82.
  14. Cadenas, Erasmo & Rivera, Wilfrido, 2010. "Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model," Renewable Energy, Elsevier, vol. 35(12), pages 2732-2738.
  15. Yuewei Liu & Shenghui Zhang & Xuejun Chen & Jianzhou Wang, 2018. "Artificial Combined Model Based on Hybrid Nonlinear Neural Network Models and Statistics Linear Models—Research and Application for Wind Speed Forecasting," Sustainability, MDPI, vol. 10(12), pages 1-30, December.
  16. Drisya, G.V. & Asokan, K. & Kumar, K. Satheesh, 2018. "Diverse dynamical characteristics across the frequency spectrum of wind speed fluctuations," Renewable Energy, Elsevier, vol. 119(C), pages 540-550.
  17. Rodriguez-Hernandez, O. & Jaramillo, O.A. & Andaverde, J.A. & del Río, J.A., 2013. "Analysis about sampling, uncertainties and selection of a reliable probabilistic model of wind speed data used on resource assessment," Renewable Energy, Elsevier, vol. 50(C), pages 244-252.
  18. Nantian Huang & Chong Yuan & Guowei Cai & Enkai Xing, 2016. "Hybrid Short Term Wind Speed Forecasting Using Variational Mode Decomposition and a Weighted Regularized Extreme Learning Machine," Energies, MDPI, vol. 9(12), pages 1-19, November.
  19. Akçay, Hüseyin & Filik, Tansu, 2017. "Short-term wind speed forecasting by spectral analysis from long-term observations with missing values," Applied Energy, Elsevier, vol. 191(C), pages 653-662.
  20. De Giorgi, Maria Grazia & Ficarella, Antonio & Tarantino, Marco, 2011. "Assessment of the benefits of numerical weather predictions in wind power forecasting based on statistical methods," Energy, Elsevier, vol. 36(7), pages 3968-3978.
  21. Cao, Qing & Ewing, Bradley T. & Thompson, Mark A., 2012. "Forecasting wind speed with recurrent neural networks," European Journal of Operational Research, Elsevier, vol. 221(1), pages 148-154.
  22. Koo, Junmo & Han, Gwon Deok & Choi, Hyung Jong & Shim, Joon Hyung, 2015. "Wind-speed prediction and analysis based on geological and distance variables using an artificial neural network: A case study in South Korea," Energy, Elsevier, vol. 93(P2), pages 1296-1302.
  23. Flores, P. & Tapia, A. & Tapia, G., 2005. "Application of a control algorithm for wind speed prediction and active power generation," Renewable Energy, Elsevier, vol. 30(4), pages 523-536.
  24. Chen, Kuilin & Yu, Jie, 2014. "Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach," Applied Energy, Elsevier, vol. 113(C), pages 690-705.
  25. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
  26. Lazić, Lazar & Pejanović, Goran & Živković, Momčilo, 2010. "Wind forecasts for wind power generation using the Eta model," Renewable Energy, Elsevier, vol. 35(6), pages 1236-1243.
  27. López, P. & Velo, R. & Maseda, F., 2008. "Effect of direction on wind speed estimation in complex terrain using neural networks," Renewable Energy, Elsevier, vol. 33(10), pages 2266-2272.
  28. Hao Zhen & Dongxiao Niu & Min Yu & Keke Wang & Yi Liang & Xiaomin Xu, 2020. "A Hybrid Deep Learning Model and Comparison for Wind Power Forecasting Considering Temporal-Spatial Feature Extraction," Sustainability, MDPI, vol. 12(22), pages 1-24, November.
  29. Lars Ødegaard Bentsen & Narada Dilp Warakagoda & Roy Stenbro & Paal Engelstad, 2023. "A Unified Graph Formulation for Spatio-Temporal Wind Forecasting," Energies, MDPI, vol. 16(20), pages 1-23, October.
  30. Vladimir Simankov & Pavel Buchatskiy & Semen Teploukhov & Stefan Onishchenko & Anatoliy Kazak & Petr Chetyrbok, 2023. "Review of Estimating and Predicting Models of the Wind Energy Amount," Energies, MDPI, vol. 16(16), pages 1-24, August.
  31. Shah, Kamran Ali & Meng, Fantai & Li, Ye & Nagamune, Ryozo & Zhou, Yarong & Ren, Zhengru & Jiang, Zhiyu, 2021. "A synthesis of feasible control methods for floating offshore wind turbine system dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
  32. Abdel-Aal, R.E. & Elhadidy, M.A. & Shaahid, S.M., 2009. "Modeling and forecasting the mean hourly wind speed time series using GMDH-based abductive networks," Renewable Energy, Elsevier, vol. 34(7), pages 1686-1699.
  33. Cadenas, Erasmo & Rivera, Wilfrido, 2007. "Wind speed forecasting in the South Coast of Oaxaca, México," Renewable Energy, Elsevier, vol. 32(12), pages 2116-2128.
  34. Guo, Zhenhai & Zhao, Jing & Zhang, Wenyu & Wang, Jianzhou, 2011. "A corrected hybrid approach for wind speed prediction in Hexi Corridor of China," Energy, Elsevier, vol. 36(3), pages 1668-1679.
  35. Erdong Zhao & Jing Zhao & Liwei Liu & Zhongyue Su & Ning An, 2015. "Hybrid Wind Speed Prediction Based on a Self-Adaptive ARIMAX Model with an Exogenous WRF Simulation," Energies, MDPI, vol. 9(1), pages 1-20, December.
  36. Zhang, Yu & Li, Yanting & Zhang, Guangyao, 2020. "Short-term wind power forecasting approach based on Seq2Seq model using NWP data," Energy, Elsevier, vol. 213(C).
  37. Masseran, Nurulkamal, 2016. "Modeling the fluctuations of wind speed data by considering their mean and volatility effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 777-784.
  38. Alonzo, Bastien & Tankov, Peter & Drobinski, Philippe & Plougonven, Riwal, 2020. "Probabilistic wind forecasting up to three months ahead using ensemble predictions for geopotential height," International Journal of Forecasting, Elsevier, vol. 36(2), pages 515-530.
  39. Flavie Didier & Yong-Chao Liu & Salah Laghrouche & Daniel Depernet, 2024. "A Comprehensive Review on Advanced Control Methods for Floating Offshore Wind Turbine Systems above the Rated Wind Speed," Energies, MDPI, vol. 17(10), pages 1-33, May.
  40. Tascikaraoglu, A. & Uzunoglu, M., 2014. "A review of combined approaches for prediction of short-term wind speed and power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 243-254.
  41. Yuan, Shengxi & Kocaman, Ayse Selin & Modi, Vijay, 2017. "Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente," Renewable Energy, Elsevier, vol. 105(C), pages 167-174.
  42. Pei Du & Yu Jin & Kequan Zhang, 2016. "A Hybrid Multi-Step Rolling Forecasting Model Based on SSA and Simulated Annealing—Adaptive Particle Swarm Optimization for Wind Speed," Sustainability, MDPI, vol. 8(8), pages 1-25, August.
  43. Maria Grazia De Giorgi & Stefano Campilongo & Antonio Ficarella & Paolo Maria Congedo, 2014. "Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)," Energies, MDPI, vol. 7(8), pages 1-22, August.
  44. Turbelin, Grégory & Ngae, Pierre & Grignon, Michel, 2009. "Wavelet cross-correlation analysis of wind speed series generated by ANN based models," Renewable Energy, Elsevier, vol. 34(4), pages 1024-1032.
  45. Jiang, Ping & Wang, Yun & Wang, Jianzhou, 2017. "Short-term wind speed forecasting using a hybrid model," Energy, Elsevier, vol. 119(C), pages 561-577.
  46. José Carlos Palomares-Salas & Agustín Agüera-Pérez & Juan José González de la Rosa & José María Sierra-Fernández & Antonio Moreno-Muñoz, 2013. "Exogenous Measurements from Basic Meteorological Stations for Wind Speed Forecasting," Energies, MDPI, vol. 6(11), pages 1-19, November.
  47. De Giorgi, Maria Grazia & Ficarella, Antonio & Tarantino, Marco, 2011. "Error analysis of short term wind power prediction models," Applied Energy, Elsevier, vol. 88(4), pages 1298-1311, April.
  48. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
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