An optimized mean variance estimation method for uncertainty quantification of wind power forecasts
- Author
- KHOSRAVI, Abbas1 ; NAHAVANDI, Saeid1
[1] Centre for Intelligent Systems Research (CISR), Deakin University, Waurn Ponds Campus, Locked Bag 20000, Geelong, Victoria 3220, Australia - Source
Electrical power & energy systems. 2014, Vol 61, pp 446-454, 9 p ; ref : 30 ref
- CODEN
- IEPSDC
- ISSN
- 0142-0615
- Scientific domain
- Electrical engineering
- Publisher
- Elsevier, Oxford
- Publication country
- United Kingdom
- Document type
- Article
- Language
- English
- Author keyword
- Mean-variance Prediction interval Uncertainty Wind farm
- Keyword (fr)
- Algorithme apprentissage Champ éoliennes Energie éolienne Etude expérimentale Evaluation performance Intervalle confiance Optimisation Production énergie électrique Réseau neuronal Australie Océanie
- Keyword (en)
- Learning algorithm Windfarm Wind energy Experimental study Performance evaluation Confidence interval Optimization Electric power production Neural network Australia Oceania
- Keyword (es)
- Algoritmo aprendizaje Campo generator aire Energía eólica Estudio experimental Evaluación prestación Intervalo confianza Optimización Producción energía eléctrica Red neuronal Australia Oceania
- Classification
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D05 Electrical engineering. Electrical power engineering / 001D05I Electrical power engineering / 001D05I02 Electric power plants / 001D05I02D Non classical power plants / 001D05I02D3 Wind power plants
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D05 Electrical engineering. Electrical power engineering / 001D05I Electrical power engineering / 001D05I02 Electric power plants / 001D05I02E Miscellaneous
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D05 Electrical engineering. Electrical power engineering / 001D05I Electrical power engineering / 001D05I03 Direct energy conversion and energy accumulation / 001D05I03G Miscellaneous
- Pascal
- 001 Exact sciences and technology / 001D Applied sciences / 001D06 Energy / 001D06C Natural energy / 001D06C04 Wind energy
- Discipline
- Electrical engineering. Electroenergetics Energy
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 28517339
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1016/j.ijepes.2014.03.060 
https://dx.doi.org/10.1016/j.ijepes.2014.03.060
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