In this article we describe preliminary results for a general data acquisition and management platform applied to system level solar farm energy optimization. The system optimization takes into account weather, solar radiance, sky cloud coverage, and solar panel characteristics. Despite continuous improvement in photovoltaic (PV) systems, the generated power of many installations is underperforming due to factors like: light obstruction, orientation and tilt of the solar panels, variation in manufacturing and installation process and debris or soiling on the solar panels. To overcome the above challenges, we leverage the capabilities of an energy management analytic platform to monitor in real time the power generation from solar panels under real operating conditions. The generated power of the solar panel is correlated with predictive weather models where the influence of sky coverage, temperature and opacity of air are integrated in physical models to predict the solar panel performance. Furthermore, it is recognized that in large scale photovoltaics system the generated power is dependent on the performance of individual cells and solar panels. Analyzing spatial and temporal trends of individual solar panels and combining it with real time power performance enable an increased visibility in the PV system performance and optimization through power management of the individual solar panel.

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