Improvements in the predictions for the photovoltaic system performance of the Mediterranean regions

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%.

[1]  N. Scarlat,et al.  Renewable energy policy framework and bioenergy contribution in the European Union – An overview from National Renewable Energy Action Plans and Progress Reports , 2015 .

[2]  M. G. De Giorgi,et al.  Comparison of strategies for multi-step ahead photovoltaic power forecasting models based on hybrid group method of data handling networks and least square support vector machine , 2016 .

[3]  J. Hay,et al.  Estimating Solar Irradiance on Inclined Surfaces: A Review and Assessment of Methodologies , 1985 .

[4]  Klaus Vajen,et al.  Comparison of Different Sources of Meteorological Data for Central Asia and Russia , 2010 .

[5]  A. D. Jones,et al.  A thermal model for photovoltaic systems , 2001 .

[6]  Tuza Olukan,et al.  A Comparative Analysis of PV Module Temperature Models , 2014 .

[7]  M. G. De Giorgi,et al.  Performance measurements of monocrystalline silicon PV modules in South-eastern Italy , 2013 .

[8]  Rahman Saidur,et al.  Grid-connected PV systems installed on institutional buildings: Technology comparison, energy analysis and economic performance , 2016 .

[9]  Roohollah Fadaeinedjad,et al.  Temperature of a photovoltaic module under the influence of different environmental conditions – experimental investigation , 2016 .

[10]  Marc Zebisch,et al.  Wind effect on PV module temperature: Analysis of different techniques for an accurate estimation , 2013 .

[11]  A. Dolara,et al.  Comparison of different physical models for PV power output prediction , 2015 .

[12]  Dazhi Yang,et al.  Solar radiation on inclined surfaces: Corrections and benchmarks , 2016 .

[13]  John K. Kaldellis,et al.  Temperature and wind speed impact on the efficiency of PV installations. Experience obtained from outdoor measurements in Greece , 2014 .

[14]  Yoram Krozer,et al.  Cost and benefit of renewable energy in the European Union , 2013 .

[15]  John Boland,et al.  Evaluating tilted plane models for solar radiation using comprehensive testing procedures, at a southern hemisphere location , 2013 .

[16]  Sivasankari Sundaram,et al.  Performance evaluation and validation of 5 MWp grid connected solar photovoltaic plant in South India , 2015 .

[17]  M. Malvoni,et al.  Data on Support Vector Machines (SVM) model to forecast photovoltaic power , 2016, Data in brief.

[18]  Kap-Chun Yoon,et al.  Evaluation of hourly solar radiation on inclined surfaces at Seoul by Photographical Method , 2014 .

[19]  Maria Grazia De Giorgi,et al.  Error analysis of hybrid photovoltaic power forecasting models: A case study of mediterranean climate , 2015 .

[20]  Samy A. Khalil,et al.  Evaluation of transposition models of solar irradiance over Egypt , 2016 .

[21]  Dezso Sera,et al.  Investigation of wind speed cooling effect on PV panels in windy locations , 2016 .

[22]  Nate Blair,et al.  Validation of multiple tools for flat plate photovoltaic modeling against measured data , 2014, 2014 IEEE 40th Photovoltaic Specialist Conference (PVSC).

[23]  Maria Grazia De Giorgi,et al.  Photovoltaic forecast based on hybrid PCA-LSSVM using dimensionality reducted data , 2016, Neurocomputing.

[24]  J. Michalsky,et al.  Modeling daylight availability and irradiance components from direct and global irradiance , 1990 .

[25]  J. Hay Calculation of monthly mean solar radiation for horizontal and inclined surfaces , 1979 .

[26]  S. S. Chandel,et al.  Performance analysis of a 190 kWp grid interactive solar photovoltaic power plant in India , 2013 .

[27]  Alistair B. Sproul,et al.  Photovoltaic (PV) performance modelling in the absence of onsite measured plane of array irradiance (POA) and module temperature , 2016 .

[28]  Maria Grazia De Giorgi,et al.  Photovoltaic power forecasting using statistical methods: impact of weather data , 2014 .

[29]  M Malvoni,et al.  Data on photovoltaic power forecasting models for Mediterranean climate , 2016, Data in brief.

[30]  Yanping Du,et al.  Evaluation of photovoltaic panel temperature in realistic scenarios , 2016 .

[31]  J. Duffie,et al.  Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation , 1982 .

[32]  Eleni Kaplani,et al.  Thermal modelling and experimental assessment of the dependence of PV module temperature on wind velocity and direction, module orientation and inclination , 2014 .

[33]  Clifford W. Hansen,et al.  Evaluation of Global Horizontal Irradiance to Plane-of-Array Irradiance Models at Locations Across the United States , 2015, IEEE Journal of Photovoltaics.

[34]  P. Ineichen,et al.  A new simplified version of the perez diffuse irradiance model for tilted surfaces , 1987 .

[35]  J. Carretero,et al.  Models to predict the operating temperature of different photovoltaic modules in outdoor conditions , 2015 .