Improvements in the predictions for the photovoltaic system performance of the Mediterranean regions. (15th November 2016)

• Record Type: Journal Article
• Authors: Malvoni, M.; Fiore, M.C.; Maggiotto, G.; Mancarella, L.; Quarta, R.; Radice, V.; Congedo, P.M.; De Giorgi, M.G.
• Is Part Of: Energy conversion and management. Volume 128(2016)
• Page Start: 191
• Page End: 202
• Publication Date: 2016-11-15
• Subjects: Plane of array irradiance -- Meteo data -- PVsyst -- Module temperature -- Wind speed; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2016.09.069
• Languages: English
• ISSNs: 0196-8904

Abstract

Highlights: Perez model returns PV energy predictions higher than the Hay/Davies model. Suitable weather data is needed when meteo data on-site are not available. The geographic area of the meteo station impacts on the PV energy estimations. The rural areas are more suitable to plan new solar systems. A wind speed up to 4 m/s may increase PV energy output up to 1%. Abstract: The performance assessment of photovoltaic (PV) systems is a complex process. Several meteorological data sources are available to evaluate the PV system generation. Different computing models can be applied to determinate the solar irradiance on the plane of the array (POA). The cooling effect of the PV module due to the wind speed should not be neglected. The present study may support several users to perform more accurate PV energy predictions, providing important suggestions to develop future PV system projects with more high reliability. Perez and Hay-Davies models for the computing of the irradiance on tilted surfaces are combined with three meteorological datasets, characterized by different monitoring period and meteo station location, to estimate the POA irradiance, the module temperature and PV energy output for a PV system located in the Mediterranean climate area. Prediction results are performed by the PVsyst tool and compared with the actual data. Simulations are carried out taking into account the wind effects on the PV module performance. Results demonstrate that the geographic features of the location, in which the weather station is located, have higher impact on the estimations of the PV system performance than the distance between the PV system and the meteo station. Perez and Hay-Davies models provide predictions of the PV energy and the module temperature with a difference up to 3% and 1% respectively. Yearly average wind speed in the range 2–4 m/s fosters a cooling effect up to 3% higher than one due to the wind magnitude less of 2 m/s, increasing the PV energy up to 1%.