Wind energy forecasting with neural networks: a literature review
Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecast...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/129113 |
| Acceso en línea: | https://hdl.handle.net/2117/129113 https://dx.doi.org/10.13053/CyS-22-4-3081 |
| Access Level: | acceso abierto |
| Palabra clave: | Machine learning Neural networks (Computer science) Forecasting Wind power Wind power forecast Wind speed forecast Short-term prediction Deep learning Literature review Aprenentatge automàtic Xarxes neuronals (Informàtica) Previsió Energia eòlica Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic Àrees temàtiques de la UPC::Energies::Energia eòlica |
| Sumario: | Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these methods are being used commercially around the world. But one family of new methods for wind power fore castingis surging based on Machine Learning Deep Learning techniques. This paper analyses the characteristics of the Wind Speed time series data and performs a literature review of recently published works of wind power forecasting using Machine Learning approaches (neural and deep learning networks), which have been published in the last few years. |
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