Prediction in Photovoltaic Power by Neural Networks

Antonello Rosato, Rosa Altilio, Rodolfo Araneo and Massimo Panella
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Antonello Rosato: Department of Information Engineering, Electronics and Telecommunications, University of Rome “La Sapienza”, via Eudossiana, 18, Rome 00184, Italy
Rosa Altilio: Department of Information Engineering, Electronics and Telecommunications, University of Rome “La Sapienza”, via Eudossiana, 18, Rome 00184, Italy
Rodolfo Araneo: Electrical Engineering Division of Department of Astronautical, Electrical and Energy Engineering, University of Rome “La Sapienza”, via Eudossiana, 18, Rome 00184, Italy
Massimo Panella: Department of Information Engineering, Electronics and Telecommunications, University of Rome “La Sapienza”, via Eudossiana, 18, Rome 00184, Italy

Energies, 2017, vol. 10, issue 7, 1-25

Abstract: The ability to forecast the power produced by renewable energy plants in the short and middle term is a key issue to allow a high-level penetration of the distributed generation into the grid infrastructure. Forecasting energy production is mandatory for dispatching and distribution issues, at the transmission system operator level, as well as the electrical distributor and power system operator levels. In this paper, we present three techniques based on neural and fuzzy neural networks, namely the radial basis function, the adaptive neuro-fuzzy inference system and the higher-order neuro-fuzzy inference system, which are well suited to predict data sequences stemming from real-world applications. The preliminary results concerning the prediction of the power generated by a large-scale photovoltaic plant in Italy confirm the reliability and accuracy of the proposed approaches.

Keywords: embedding technique; power forecasting; photovoltaic power plant; neural and fuzzy neural network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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