Single and Blended Models for Day-Ahead Photovoltaic Power Forecasting
| Autor: | Luis Alfredo Fernández-Jiménez, Ruben Urraca, J. Antonanzas, Alvaro Aldama, Alpha Pernia-Espinoza, Francisco Javier Martinez-de-Pison |
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| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science 020209 energy Photovoltaic system Cloud computing 02 engineering and technology 021001 nanoscience & nanotechnology Grid Solar energy Industrial engineering Solar power forecasting Solar Resource Physics::Space Physics 0202 electrical engineering electronic engineering information engineering Astrophysics::Solar and Stellar Astrophysics Astrophysics::Earth and Planetary Astrophysics Natural variability 0210 nano-technology business Solar power |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319596495 HAIS |
| DOI: | 10.1007/978-3-319-59650-1_36 |
| Popis: | Solar power forecasts are gaining continuous importance as the penetration of solar energy into the grid rises. The natural variability of the solar resource, joined to the difficulties of cloud movement modeling, endow solar power forecasts with a certain level of uncertainty. Important efforts have been carried out in the field to reduce as much as possible the errors. Various approaches have been followed, being the predominant nowadays the use of statistical techniques to model production. |
| Databáze: | OpenAIRE |
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