It is well known that the knowledge of solar radiation represents a key for managing photovoltaic (PV) plants. In a smart grid scenario to predict the energy production can be considered a milestone. However, the unsteadiness of the weather phenomena makes the prediction of the energy produced by the solar radiation conversion process a difficult task. Starting from this considerations, the use of the data collected in the past represents only the first step in order to evaluate the variability both in a daily and seasonal fashion. In order to have a stronger dataset a multi-year observation is mandatory. In this paper, several autoregressive models are challenged on a two-year ground global horizontal radiation dataset measured in Milan, and the results are compared with those of simple predictor.
Statistical models approach for solar radiation prediction / S. Ferrari, M. Lazzaroni, V. Piuri, L. Cristaldi, M. Faifer - In: 2013 IEEE International instrumentation and measurement technology conference : I2MTC 2013 : Instrumentation and measurement for life : proceedings : 6-9 May 2013, MinneapolisPiscataway (New Jersey) : IEEE, 2013. - ISBN 978-1-4673-4621-4. - pp. 1734-1739 (( convegno Instrumentation and measurement technology conference : I2MTC 2013 tenutosi a Minneapolis (Minnesota) nel 2013 [10.1109/I2MTC.2013.6555712].
Statistical models approach for solar radiation prediction
S. FerrariPrimo
;M. LazzaroniSecondo
;V. Piuri;
2013
Abstract
It is well known that the knowledge of solar radiation represents a key for managing photovoltaic (PV) plants. In a smart grid scenario to predict the energy production can be considered a milestone. However, the unsteadiness of the weather phenomena makes the prediction of the energy produced by the solar radiation conversion process a difficult task. Starting from this considerations, the use of the data collected in the past represents only the first step in order to evaluate the variability both in a daily and seasonal fashion. In order to have a stronger dataset a multi-year observation is mandatory. In this paper, several autoregressive models are challenged on a two-year ground global horizontal radiation dataset measured in Milan, and the results are compared with those of simple predictor.File | Dimensione | Formato | |
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