A photovoltaic (PV) plant model is presented. It is based on a detailed electrothermal description of the panels forming strings that, in turn, form the power plant. It accounts for environmental working conditions, such as temperature and wind speed, and specific plant configuration, such as plant topology and power losses due to interconnections. The input variables of the model are the ambient temperature, irradiance, and wind speed. The model derives the working temperature of the panel taking into account also the power conversion performed by the panel; the electrical operating point is determined by simulating the actions done by the maximum power point tracker that operates at plant level. This model has been tested using a large database of experimental data from industrial PV plants characterized by power levels ranging from 250 kW to 1 MW. As shown, the model is capable to predict power production when “fed” by forecast irradiance, ambient temperature, and wind speed data.

Model of Photovoltaic Power Plants for Performance Analysis and Production Forecast

BIZZARRI, FEDERICO;BONGIORNO, MAGDA EURINICE JOSEPHINE;BRAMBILLA, ANGELO MAURIZIO;GRUOSSO, GIAMBATTISTA;STORTI GAJANI, GIANCARLO
2013-01-01

Abstract

A photovoltaic (PV) plant model is presented. It is based on a detailed electrothermal description of the panels forming strings that, in turn, form the power plant. It accounts for environmental working conditions, such as temperature and wind speed, and specific plant configuration, such as plant topology and power losses due to interconnections. The input variables of the model are the ambient temperature, irradiance, and wind speed. The model derives the working temperature of the panel taking into account also the power conversion performed by the panel; the electrical operating point is determined by simulating the actions done by the maximum power point tracker that operates at plant level. This model has been tested using a large database of experimental data from industrial PV plants characterized by power levels ranging from 250 kW to 1 MW. As shown, the model is capable to predict power production when “fed” by forecast irradiance, ambient temperature, and wind speed data.
2013
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/685502
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