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  • Search: subject:"Wind power forecasting"
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Year of publication
Subject
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Wind power forecasting 4 wind power forecasting 4 Multi-variate prediction 2 Performance evaluation and comparison 2 Short and long term prediction 2 Time series to frequency transformation 2 Unsupervised machine learning 2 ARIMA 1 Artificial Neural Network (ANN) 1 Artificial intelligence 1 Diebold-Mariano (DM) test 1 Energy forecasting 1 Error analysis 1 Forecasting competition 1 Forecasting model 1 Künstliche Intelligenz 1 LS-SVM 1 Least-Squares Support Vector Machine (LS-SVM) 1 Load forecasting 1 Lévy a-stable distribution 1 Prognoseverfahren 1 Stable process 1 Statistical analysis 1 Time series analysis 1 Wind energy 1 Wind power generation 1 Wind turbine 1 Windenergie 1 Windenergieanlage 1 Zeitreihenanalyse 1 asymmetric DM test 1 augmented DM test 1 back propagation neural network 1 check function 1 continuous ranked probability score 1 density forecasting 1 enhanced particle swarm optimization algorithm 1 evaluation criteria 1 fuzzy group 1 hybrid forecasting method 1
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Online availability
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Free 9 CC license 1
Type of publication
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Article 7 Book / Working Paper 2
Type of publication (narrower categories)
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Article 1 Article in journal 1 Aufsatz in Zeitschrift 1 Conference paper 1 Konferenzbeitrag 1
Language
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Undetermined 7 English 2
Author
All
Bordin, Chiara 2 Mishra, Sambeet 2 Palu, Ivo 2 Taharaguchi, Kota 2 Anastasiades, Georgios 1 Bruninx, Kenneth 1 Campilongo, Stefano 1 Chang, Wen-Yeau 1 Chen, Hao 1 Congedo, Paolo Maria 1 D'haeseleer, William 1 Delarue, Erik 1 Fan, Shu 1 Ficarella, Antonio 1 Giorgi, Maria Grazia De 1 Hong, Tao 1 Lai, Kin Keung 1 McSharry, Patrick 1 Niu, Dongxiao 1 Pinson, Pierre 1 Wan, Qiulan 1 Wang, Qiang 1 Wang, Yurong 1 Zhang, Qian 1 Zhang, Xuebin 1
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Institution
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Hugo Steinhaus Center for Stochastic Methods, Politechnika Wrocławska 1 Robert Schuman Centre for Advanced Studies (RSCAS), European University Institute 1
Published in...
All
Energies 5 Energy Reports 1 Energy reports 1 HSC Research Reports 1 RSCAS Working Papers 1
Source
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RePEc 7 ECONIS (ZBW) 1 EconStor 1
Showing 1 - 9 of 9
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Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature
Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; … - In: Energy Reports 6 (2020) 3, pp. 273-286
Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the...
Persistent link: https://www.econbiz.de/10012652360
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Cover Image
Comparison of deep learning models for multivariate prediction of time series wind power generation and temperature
Mishra, Sambeet; Bordin, Chiara; Taharaguchi, Kota; … - In: Energy reports 6 (2020) 3, pp. 273-286
Wind power experienced a substantial growth over the past decade especially because it has been seen as one of the best ways towards meeting climate change and emissions targets by many countries. Since wind power is not fully dispatchable, the accuracy of wind forecasts is a key element for the...
Persistent link: https://www.econbiz.de/10012183091
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Comparison Between Wind Power Prediction Models Based on Wavelet Decomposition with Least-Squares Support Vector Machine (LS-SVM) and Artificial Neural Network (ANN)
Giorgi, Maria Grazia De; Campilongo, Stefano; … - In: Energies 7 (2014) 8, pp. 5251-5272
A high penetration of wind energy into the electricity market requires a parallel development of efficient wind power … forecasting models. Different hybrid forecasting methods were applied to wind power prediction, using historical data and …
Persistent link: https://www.econbiz.de/10010886253
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Refined Diebold-Mariano Test Methods for the Evaluation of Wind Power Forecasting Models
Chen, Hao; Wan, Qiulan; Wang, Yurong - In: Energies 7 (2014) 7, pp. 4185-4198
The scientific evaluation methodology for the forecast accuracy of wind power forecasting models is an important issue … in the domain of wind power forecasting. However, traditional forecast evaluation criteria, such as Mean Squared Error … practical evaluation of wind power forecasting models. It is concluded that the two refined DM tests can provide reference to …
Persistent link: https://www.econbiz.de/10010790945
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Global Energy Forecasting Competition 2012
Hong, Tao; Pinson, Pierre; Fan, Shu - Hugo Steinhaus Center for Stochastic Methods, … - 2013
forecasting and wind power forecasting, with details on the aspects of the problem, the data, and a summary of the methods used by …
Persistent link: https://www.econbiz.de/10011165887
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Quantile Forecasting of Wind Power Using Variability Indices
Anastasiades, Georgios; McSharry, Patrick - In: Energies 6 (2013) 2, pp. 662-695
Wind power forecasting techniques have received substantial attention recently due to the increasing penetration of …
Persistent link: https://www.econbiz.de/10010668185
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Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method
Chang, Wen-Yeau - In: Energies 6 (2013) 9, pp. 4879-4896
-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network …
Persistent link: https://www.econbiz.de/10010692413
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Statistical description of the error on wind power forecasts via a Lévy α-stable distribution
Bruninx, Kenneth; Delarue, Erik; D'haeseleer, William - Robert Schuman Centre for Advanced Studies (RSCAS), … - 2013
As the share of wind power in the electricity system rises, the limited predictability of wind power generation becomes increasingly critical for operating a reliable electricity system. In most operational & economic models, the wind power forecast error (WPFE) is often assumed to have a...
Persistent link: https://www.econbiz.de/10010718045
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A Fuzzy Group Forecasting Model Based on Least Squares Support Vector Machine (LS-SVM) for Short-Term Wind Power
Zhang, Qian; Lai, Kin Keung; Niu, Dongxiao; Wang, Qiang; … - In: Energies 5 (2012) 9, pp. 3329-3346
Many models have been developed to forecast wind farm power output. It is generally difficult to determine whether the performance of one model is consistently better than that of another model under all circumstances. Motivated by this finding, we aimed to integrate groups of models into an...
Persistent link: https://www.econbiz.de/10010675982
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