1. Power Forecasting of a Photovoltaic Plant Located in ENEA Casaccia Research Center.
- Author
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Radicioni, Martina, Lucaferri, Valentina, De Lia, Francesco, Laudani, Antonino, Lo Presti, Roberto, Lozito, Gabriele Maria, Riganti Fulginei, Francesco, Schioppo, Riccardo, Tucci, Mario, Hervás Martínez, Cesar, Salcedo-Sanz, Sancho, and Gutiérrez, Pedro Antonio
- Subjects
PHOTOVOLTAIC power systems ,ARTIFICIAL neural networks ,MAXIMUM power point trackers ,SUSTAINABLE development ,RESEARCH institutes ,BUILDING-integrated photovoltaic systems ,ATMOSPHERIC temperature - Abstract
This work proposes an Artificial Neural Network (ANN) able to provide an accurate forecasting of power produced by photovoltaic (PV) plants. The ANN is customized on the basis of the particular season of the year. An accurate analysis of input variables, i.e., solar irradiance, temperature and air humidity, carried out by means of Pearson Correlation, has allowed to select, day by day, the most suitable set of inputs and ANN architecture also to reduce the necessity of large computational resource. Thus, features are added to the ANN as needed, avoiding waste of computational resources. The method has been validated through data collected from a PV plant installed in ENEA (National agency for new technologies, energy and sustainable economic development) Research Center, located in Casaccia, Rome (Italy). The developed strategy is able to furnish accurate predictions even in the case of strong irregularities of solar irradiance, providing accurate results in rapidly changing scenarios. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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