INFLUENCE OF SOLAR PANELS TILT ANGLE AND GROUND COVER RATIO ON PV PLANT PERFORMANCE

One of the main factors affecting the photovoltaic (PV) plant power is the self-shading from adjacent rows of solar panels. Due to the peculiarities of the electric connections of photovoltaic cells in PV modules and the presence of bypass diodes, the partial shading is capable of significantly decreasing the PV plant power at certain times of the day. The partial shading of solar panels effects in different ways on the energy production in cases of the vertical placement of PV modules in the panel’s frame (portrait mounting) and the horizontal placement of PV modules (landscape mounting). This work presents a novel analytical approach for determining of the inter-row shading effect on the large PV plant efficiency which is applicable for any seasonal period of PV operation. The initial data for calculations are the hourly generation of shaded and fully illuminated solar panels. On the base of these data, we have calculated the power factor that describes the dependence of the module's electrical power on the shading degree. The power factor is used to determine the amount of radiation entering the panel’s tilted surface during each day of the operation period. The long-term meteorological data for the main radiation components and one of the known anisotropic radiation model are necessary for these calculations. The main calculations result is the distribution maps for the average daily energy output which first proposed in our work. These maps have the form of contour graphs which build in the coordinates “the ground cover ratio – the tilt angle” as construction parameters. Using this maps one can find the optimal ratios of these parameters for two types of optimization problems: (1) ensure the maximum possible output under given installed PV power and (2) the determination of the most rational use of a land plot for PV plant, i.e. the obtaining of maximum PV production per unit of land area. The advantage of the analytical approach is that it allows scaling to large PV systems without increasing the computation time. As examples, the paper performs the optimization calculations based on the monitoring output data for the commercial PV plant located in Germany and on the experimental partial shading data in Odessa region.

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