A modern renewable energy forecasting system blends physical models with artificial intelligence to aid in system operation and grid integration. This paper describes such a system being developed for the Shagaya Renewable Energy Park, which is being developed by the State of Kuwait. The park contains wind turbines, photovoltaic panels, and concentrated solar renewable energy technologies with storage capabilities. The fully operational Kuwait Renewable Energy Prediction System (KREPS) employs artificial intelligence (AI) in multiple portions of the forecasting structure and processes, both for short-range forecasting (i.e., the next six hours) as well as for forecasts several days out. These AI methods work synergistically with the dynamical/physical models employed. This paper briefly describes the methodology used for each of the AI methods, how they are blended, and provides a preliminary assessment of their relative value to the prediction system. Each operational AI component adds value to the system. KREPS is an example of a fully integrated state-of-the-science forecasting system for renewable energy.

Using 30 years of satellite observations, two sand and dust storms (SDS) source locations (hotspots) were detected on the southern side of the Mesopotamian Flood Plain. Around 40 million people in the region are affected by the two hotspots, including populations in Iraq, Iran, Kuwait, Saudi Arabia, Qatar, Bahrain, and Emirates. Both hotspots encompass roughly 8212 km² and contribute 11% to 85% in 2005 and 2021, respectively, of the total SDS in the region. Dust physical (particle surface area and size percentages) and chemical (mineralogy, major and trace elements, and radionuclides) properties show close similarities between source and downwind samples during SDS originated solely from the two hotspots. Deposited dust size particles show a finning trend towards the north in the Middle East compared to the south. A comprehensive assessment of the chemical and physical properties of soil and dust samples was conducted as an essential step in developing and implementing a mitigation plan in order to establish a success story in reducing SDS, improving air quality, and benefiting the gulf countries and neighboring regions.