Photovoltaic (PV) performance predictions are important to accurately assess the efficiency of any PV technology. In this study, we confront outdoor data with no less than 48 couples obtained by combining eight models of the thermal behavior with six electrical formulas. Calculations are confronted to the power produced by a 2 kWp grid-connected monocrystalline Si photovoltaic plant (GCPV) installed on the rooftop in the Faculty of Science Semlalia Marrakech, Morocco (latitude 31.6497 °N, longitude 8.0169 °W). The measured meteorological parameters (irradiance and air temperature), electrical data (DC power), and modules temperature data from one year have been used. The approach to evaluate the quality of each couple of models is new since this work uses the combination of (i) the best mix of correlation coefficient (R²) and root mean square error (RMSE), and (ii) the number of points validated by the model within a 99% confidence interval. Among the eight thermal behavior models, we propose ourselves a dynamic one which takes into consideration inertia which is usually ignored in stationary models.Keywords Grid-connected PV, PV DC-power measurements, Module temperature measurements, PV DC-power models, Module temperature models, Combinations of DC-power and module temperature models.

In this paper, we estimate expected monthly averages of daily energy yields with methods which use solar maps published by weather services dedicated to solar energy. We present a comparison of monthly averages of PV daily yields calculated with our own models as well as with values obtained from international databases. In terms of methodology, our paper refers always to the results of an hour-by-hour simulation software. Whatever picture we take, we find that linear "simple models" tend always to overestimate yields and we explain why. We propose a non-linear model which seems to be the best compromise for our future PV yields database. AbstractImproving grid-connected PV dc yields obtained with daily models. Amin Bennouna*, Noura Aarich, Noureddine Erraissi, Mohamed Akhsassi and Mustapha RaoufiDepartment of Physics, Faculty of Science Semlalia Marrakech, Cadi Ayyad University, Morocco Accepted on July 20, 2017Keywords: Photovoltaic grid-connected systems; photovoltaic yields models; monthly average of daily dc yields; yearly dc yields; comparison of photovoltaic yields; Morocco.

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