access icon openaccess Solar energy production forecasting through artificial neuronal networks, considering the Föhn, north and south winds in San Juan, Argentina

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 06/11/2018, Accepted 10/01/2019, Published 15/03/2019
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Inspec keywords: statistical analysis; load forecasting; neural nets; learning (artificial intelligence); weather forecasting; wind; photovoltaic power systems; solar power stations; sunlight

Other keywords: forecasting method; south winds; day-ahead solar irradiation curve; raw forecast; environmental variables; Föhn; power production; San Juan; artificial neuronal network; ANN; Argentina; numerical weather prediction methods; mentioned phenomena; solar energy production forecasting; calculated ideal solar irradiation curve; methodology merges statistical learning methods; extreme meteorological phenomena

Subjects: Knowledge engineering techniques; Solar power stations and photovoltaic power systems; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Probability theory, stochastic processes, and statistics; Winds and their effects in the lower atmosphere; Other topics in statistics; Neural computing techniques; Power system planning and layout; Other topics in statistics; Weather analysis and prediction

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