Journal of Solar Energy Engineering · 2014 · 12 citations · 12 references
EngineeringWeather ForecastingClimate ModelingPhotovoltaic SystemPhotovoltaicsEarth ScienceNumerical Weather PredictionModules ArrayData SciencePersistence ModelSt ModelsRenewable Energy SystemsSolar PowerEnergy ForecastingNeural NetworksForecastingSpace WeatherEnergy PredictionSolar VariabilityRooftop PhotovoltaicsSolar Radiation Management
In this paper, several models to forecast the hourly solar irradiance with a day in advance using artificial neural network techniques have been developed and analyzed. The forecast irradiance is the one incident on the plane of the modules array of a photovoltaic plant. Pure statistical (ST) models that use only local measured data and model output statistics (MOS) approaches to refine numerical weather prediction data are tested for the University of Rome “Tor Vergata” site. The performance of ST and MOS, together with the persistence model (PM), is compared. The ST models improve the performance of the PM of around 20%. The combination of ST and NWP in the MOS approach gives the best performance, improving the forecast of approximately 39% with respect to the PM.
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Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems
Elke Lorenz, Johannes Hurka, Detlev Heinemann et al. · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2009 · 693 citations
Forecasting Methodology, Engineering, Weather Forecasting +23