Abstract
The need to reduce energy consumptions and to optimize the processes of energy production has pushed the technology towards the implementation of hybrid systems for combined production of electric and thermal energies. In particular, recent researches look with interest at the installation of hybrid system PV/T. To improve the energy performance of these systems, it is necessary to know the operating temperature of the photovoltaic modules. The determination of the operating temperature <svg style="vertical-align:-3.3907pt;width:16.9px;" id="M1" height="15.8375" version="1.1" viewBox="0 0 16.9 15.8375" width="16.9" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(.017,-0,0,-.017,.062,11.55)"><path id="x1D447" d="M649 676l-22 -187l-33 -2q3 56 -12 94q-8 20 -31.5 26.5t-86.5 6.5h-74l-90 -491q-4 -23 -6 -36.5t1 -25t7 -16.5t18 -9t27 -5t41 -3l-6 -28h-286l4 28q68 5 84 18.5t28 76.5l94 491h-55q-74 0 -100.5 -6t-41.5 -23q-24 -29 -54 -98l-32 1q32 98 53 188h22q7 -18 15 -22
t37 -4h417q23 0 33.5 5t25.5 21h23z" /></g> <g transform="matrix(.012,-0,0,-.012,11.388,15.637)"><path id="x1D450" d="M383 397q0 -32 -35 -49q-12 -6 -23 8q-37 45 -84 45t-90 -71q-40 -65 -40 -167q0 -57 22 -86t59 -29q38 0 81.5 24.5t69.5 51.5l16 -21q-44 -53 -104 -84t-109 -31q-56 0 -89.5 41t-33.5 117q0 61 30 124t79 105q33 28 81 50.5t86 22.5q34 0 59 -15.5t25 -35.5z" /></g> </svg> is a key parameter for the assessment of the actual performance of photovoltaic panels. In the literature, it is possible to find different correlations that evaluate the <svg style="vertical-align:-3.3907pt;width:16.9px;" id="M2" height="15.8375" version="1.1" viewBox="0 0 16.9 15.8375" width="16.9" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(.017,-0,0,-.017,.062,11.55)"><use xlink:href="#x1D447"/></g> <g transform="matrix(.012,-0,0,-.012,11.388,15.637)"><use xlink:href="#x1D450"/></g> </svg> referring to standard test conditions and/or applying some theoretical simplifications/assumptions. Nevertheless, the application of these different correlations, for the same conditions, does not lead to unequivocal results. In this work an alternative method, based on the employment of artificial neural networks (ANNs), was proposed to predict the operating temperature of a PV module. This methodology does not require any simplification or physical assumptions. In the paper is described the ANN that obtained the best performance: a multilayer perception network. The results have been compared with experimental monitored data and with some of the most cited empirical correlations proposed by different authors.
Highlights
In the world energy scenario affected by the reduction offossil fuels supply used for the production of the electrical and thermal energy, the potential offered by renewable energy sources (RES) is strategic for the industrial countries [1]
To validate the Artificial Neural Networks (ANNs) methodology, a comparison between ANN results and the Tc calculated with same of the most cited empirical correlations was carried out extracting the Mean Absolute Error (MAE) values
In this paper, an artificial neural network approach has been proposed to determine the operative temperature of PVmodules
Summary
In the world energy scenario affected by the reduction offossil fuels supply used for the production of the electrical and thermal energy, the potential offered by renewable energy sources (RES) is strategic for the industrial countries [1]. The NOCT approach estimate Tc basing only on the passive behaviour of the PV, not taking into account at the same time the actual weather variables and the electricity production regimes of the PV module This approach neglects the fact that not all the absorbed solar irradiance is converted into electricity: generally, only 15-18% is converted into electricity; the remaining part of the insolation is transformed into heat contributing to increase the temperature cell. The heat transfer between the PV panel and the surrounding environment is driven by a global heat transfer coefficient, which describes the radiative and convective exchange processes For these reasons, in this work after a simplified description of the energy balance of a PV, which highlights the dependence of the operating temperature by some environmental parameters and by the thermo-physical properties of a PV system, the authors underline how the determination of Tc using conventional calculation procedures is often complex and difficult to solve. This method do not need exact mathematical models, can work with vague inputs and can handle nonlinearities [31]
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