On the development of mapping and forecasting capabilities of solar energy resources for the Kingdom


This talk will present our efforts to develop mapping and real-time forecasting capabilities of solar energy resources for the Kingdom. Building on our regional high-resolution data-driven atmospheric modeling system and its long-term climatology product that we have developed at KAUST as part of the Virtual Red Sea Initiative, we are exploring the most efficient approaches, in terms of computing cost, data requirements and performances, for solar energy resources mapping and forecasting making use of all available information from in-situ and satellite observations, and physics and numerics. We are currently investigating the best combinations of the computationally demanding regional general circulation atmospheric models and the much cheaper but data-dependent Machine Learning models. I will discuss the current status of these ongoing efforts and showcase the supporting real-time online visualization-analytics tools that we are developing to provide user-friendly access to the large datasets that are outputted by the systems.

This talk will present our efforts to develop mapping and real-time forecasting capabilities of solar energy resources for the Kingdom. Building on our regional high-resolution data-driven atmospheric modeling system and its long-term climatology product that we have developed at KAUST as part of the Virtual Red Sea Initiative, we are exploring the most efficient approaches, in terms of computing cost, data requirements and performances, for solar energy resources mapping and forecasting making use of all available information from in-situ and satellite observations, and physics and numerics. We are currently investigating the best combinations of the computationally demanding regional general circulation atmospheric models and the much cheaper but data-dependent Machine Learning models. I will discuss the current status of these ongoing efforts and showcase the supporting real-time online visualization-analytics tools that we are developing to provide user-friendly access to the large datasets that are outputted by the systems.

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