Abstract
The performance of solar energy production systems consisting of photovoltaic solar panels strongly depends on the location and orientation of the solar panels. Previously a computational model has been developed to predict this performance depending on location and orientation; this model allows for prior analysis of a PV system before it is actually built. In the current paper the performance of solar panels according to their location and orientation is analyzed based on empirical real world performance data, and compared to the data generated by the previously developed computational model. These empirical data have been collected from a number of solar panels at different locations and orientations day-by-day and panel-by-panel for a whole year. The data is analyzed and used to deepen the prior analysis, and to evaluate the computational model thereby generating suggestions for improvement of this model. These suggestions are a basis for an improved computational model in order to enhance the quality of prior analysis of a PV system before it is actually built. Such a pre-analysis is useful as a support for decision making by estimating how much loss different options for locations will have, before actually placing the solar panels.
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