Wind Power Prediction Based on PSO-SVR and Grey Combination Model
暂无分享,去创建一个
Yi Zhang | Hexu Sun | Yingjun Guo | Hexu Sun | Yingjun Guo | Yi Zhang
[1] Gang Zheng,et al. Ultra-Short Term Wind Power Prediction Model Based on Modified Grey Model Method for Power Control in Wind Farm , 2011 .
[2] Wei Qiao,et al. Short-Term Wind Power Prediction Using a Wavelet Support Vector Machine , 2012, IEEE Transactions on Sustainable Energy.
[3] A. Khosravi,et al. Time-series prediction of wind speed using machine learning algorithms: A case study Osorio wind farm, Brazil , 2018 .
[4] Yanbin Yuan,et al. Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine , 2017 .
[5] Eugene Fernandez,et al. Analysis of wind power generation and prediction using ANN: A case study , 2008 .
[6] Jianzhou Wang,et al. A novel hybrid model for short-term wind power forecasting , 2019, Appl. Soft Comput..
[7] Chao-Ming Huang,et al. Short-term wind power forecasting and uncertainty analysis using a hybrid intelligent method , 2017 .
[8] Jiani Heng,et al. Research and application of a hybrid model based on Meta learning strategy for wind power deterministic and probabilistic forecasting , 2018, Energy Conversion and Management.
[9] Asifullah Khan,et al. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks , 2017 .
[10] Xiaoxia Qi,et al. Deep belief network based k-means cluster approach for short-term wind power forecasting , 2018, Energy.
[11] Min Gan,et al. Design a Wind Speed Prediction Model Using Probabilistic Fuzzy System , 2012, IEEE Transactions on Industrial Informatics.
[12] Joachim Denzler,et al. Deep learning and process understanding for data-driven Earth system science , 2019, Nature.
[13] Enrico Zio,et al. An Interval-Valued Neural Network Approach for Uncertainty Quantification in Short-Term Wind Speed Prediction , 2015, IEEE Transactions on Neural Networks and Learning Systems.
[14] Ladislav Zjavka,et al. Wind speed forecast correction models using polynomial neural networks , 2015 .
[15] Abbas Khosravi,et al. Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals , 2014, IEEE Transactions on Neural Networks and Learning Systems.
[16] Ángel M. Pérez-Bellido,et al. Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction , 2009 .
[17] F. Cassola,et al. Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output , 2012 .
[18] Yanbin Li,et al. Short-term prediction of the output power of PV system based on improved grey prediction model , 2014, Proceedings of the 2014 International Conference on Advanced Mechatronic Systems.
[19] Yongqian Liu,et al. Hybrid Forecasting Model for Very-Short Term Wind Power Forecasting Based on Grey Relational Analysis and Wind Speed Distribution Features , 2014, IEEE Transactions on Smart Grid.
[20] Richard G. J. Flay,et al. Wind direction forecasting with artificial neural networks and support vector machines , 2015 .
[21] Hamidreza Zareipour,et al. A review and discussion of decomposition-based hybrid models for wind energy forecasting applications , 2019, Applied Energy.
[22] Ercan E. Kuruoglu,et al. One-day ahead wind speed/power prediction based on polynomial autoregressive model , 2017 .
[23] Robert P. Broadwater,et al. Current status and future advances for wind speed and power forecasting , 2014 .
[24] Ehab E. Elattar. Prediction of wind power based on evolutionary optimised local general regression neural network , 2014 .
[25] İnci Okumuş,et al. Current status of wind energy forecasting and a hybrid method for hourly predictions , 2016 .
[26] Enrico Zio,et al. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction , 2016, IEEE Transactions on Neural Networks and Learning Systems.
[27] Li Li,et al. A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data , 2018, Renewable Energy.
[28] N. D. Hatziargyriou,et al. Probabilistic Wind Power Forecasting Using Radial Basis Function Neural Networks , 2012, IEEE Transactions on Power Systems.
[29] Haiyan Lu,et al. A case study on a hybrid wind speed forecasting method using BP neural network , 2011, Knowl. Based Syst..
[30] Khaled M. Abo-Al-Ez,et al. A hybrid neuro-fuzzy power prediction system for wind energy generation , 2016 .
[31] Oliver Kramer,et al. Machine learning ensembles for wind power prediction , 2016 .
[32] Kit Po Wong,et al. Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine , 2014, IEEE Transactions on Power Systems.
[33] Jianzhou Wang,et al. A self-adaptive hybrid approach for wind speed forecasting , 2015 .
[34] Birgitte Bak-Jensen,et al. ARIMA-Based Time Series Model of Stochastic Wind Power Generation , 2010, IEEE Transactions on Power Systems.
[35] Duehee Lee,et al. Short-Term Wind Power Ensemble Prediction Based on Gaussian Processes and Neural Networks , 2014, IEEE Transactions on Smart Grid.
[36] Nasrudin Abd Rahim,et al. Using data-driven approach for wind power prediction: A comparative study , 2016 .
[37] Chi Dezhong,et al. Program of Wind Speed Prediction Based on Numerical Simulation with Intelligent Optimization Algorithm , 2012 .
[38] Akin Tascikaraoglu,et al. A review of combined approaches for prediction of short-term wind speed and power , 2014 .
[39] 刘峰,et al. An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed , 2015 .
[40] Saeid Nahavandi,et al. A New Fuzzy-Based Combined Prediction Interval for Wind Power Forecasting , 2016, IEEE Transactions on Power Systems.
[41] Venkata Dinavahi,et al. Direct Interval Forecast of Uncertain Wind Power Based on Recurrent Neural Networks , 2018, IEEE Transactions on Sustainable Energy.
[42] Sancho Salcedo-Sanz,et al. Accurate short-term wind speed prediction by exploiting diversity in input data using banks of artificial neural networks , 2009, Neurocomputing.
[43] Can Wan,et al. Probabilistic forecasting of wind power generation using extreme learning machine. , 2013 .
[44] Xiaoyu Yang,et al. A novel multi-information fusion grey model and its application in wear trend prediction of wind turbines , 2019, Applied Mathematical Modelling.
[45] William A. Gallus,et al. A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height , 2013 .
[46] Mehrdad Saif,et al. Application of imputation techniques and Adaptive Neuro-Fuzzy Inference System to predict wind turbine power production , 2017 .
[47] N. Safari,et al. Very Short-Term Wind Power Prediction Interval Framework via Bi-Level Optimization and Novel Convex Cost Function , 2019, IEEE Transactions on Power Systems.
[48] Paras Mandal,et al. A Hybrid Intelligent Model for Deterministic and Quantile Regression Approach for Probabilistic Wind Power Forecasting , 2014, IEEE Transactions on Power Systems.
[49] Ajit Achuthan,et al. Recursive wind speed forecasting based on Hammerstein Auto-Regressive model , 2015 .
[50] Bri-Mathias Hodge,et al. Improved Wind Power Forecasting with ARIMA Models , 2011 .
[51] H Zareipour,et al. Wind Power Prediction by a New Forecast Engine Composed of Modified Hybrid Neural Network and Enhanced Particle Swarm Optimization , 2011, IEEE Transactions on Sustainable Energy.