6533b826fe1ef96bd12834e1

RESEARCH PRODUCT

Application of adaptive models for the determination of the thermal behaviour of a photovoltaic panel

Giuseppina CiullaValerio Lo BranoMarco Beccali

subject

Set (abstract data type)Settore ING-IND/11 - Fisica Tecnica AmbientaleArtificial neural networkComputer sciencePhotovoltaic systemThermalArtificial Neural Network photovoltaic cell temperatureControl engineeringRepresentation (mathematics)SimulationEnergy (signal processing)

description

The use of reliable forecasting models for the PV temperature is necessary for a more correct evaluation of energy and economic performances. Climatic conditions certainly have a remarkable influence on thermo-electric behaviour of the PV panel but the physical system is too complex for an analytical representation. A neural-network-based approach for solar panel temperature modelling is here presented. The models were trained using a set of data collected from a test facility. Simulation results of the trained neural networks are presented and compared with those obtained with an empirical correlation.

yearjournalcountryeditionlanguage
2013-01-01
http://hdl.handle.net/10447/76552