Papier accepté à la conférence "The Third Southern African Solar Energy Conference (SASEC2015)"

Influence of Global Solar Radiation Typical Days on Error Forecasting Models

Ted Soubdhan, Cyril Voyant, Philippe Lauret


La collaboration sur la thématique de la prévision de la ressource solaire en milieu insulaire (Réunion, Guadeloupe et Corse) nous a permis de proposer un nouveau papier lors de cette conférence en Afrique du sud. Le résumé est:
"Large and frequent variations of solar radiation can be observed in tropical climates with amplitudes reaching 800 W/m² and occurring within a short time interval, from few seconds to few minutes, according to the geographical location. Such fluctuations can be due for example to the dynamic of clouds which can be very complex and depend on cloud type, size, speed and spatial distribution and, more generally, due to some specific local meteorological conditions. In this work, we have led an analysis of the error of different global solar radiation prediction models. Different predictions models where performed such as machine learning techniques (Neural Networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this study a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and tested with data from three 3 French islands: Corsica (42.15°N ; 9.08°E), Guadeloupe (16.25°N ; 61.58°W) and Reunion (21.15°S ; 55.5°E). Guadeloupe and Reunion are located in a subtropical climatic zone whereas Corsica is in a tempered climatic zone. Hence the global solar radiation variation differs significantly. The output error of the different models was quantified by the nRSME. In order to quantify the influence of the global solar radiation variation on the error forecasting models we performed a classification of typical days according to different typical days. Each class of typical day is defined by a variation of global solar radiation rate. For each class and for each location, the selected forecasting models where performed and the error was quantified. With this analysis a global solar radiation forecasting models can be selected according to the location, the global solar radiation fluctuations, hence the meteorological conditions."

https://www.researchgate.net/publication/270369794_INFLUENCE_OF_GLOBAL_SOLAR_RADIATION_TYPICAL_DAYS_ON_FORECASTING_MODELS_ERROR https://www.researchgate.net/publication/270369794_INFLUENCE_OF_GLOBAL_SOLAR_RADIATION_TYPICAL_DAYS_ON_FORECASTING_MODELS_ERROR


Rédigé par Cyril VOYANT le Mardi 21 Octobre 2014 à 13:04 | Lu 444 fois