KAUST and GE have partnered to study the feasibility of using crude oils like Arabian Super Light (ASL) to power heavy-duty gas turbines. The collaboration aims to develop turbines capable of burning crude oil directly from the ground to meet Saudi Arabia's energy security needs. The research involves building a rig at KAUST's High Pressure Combustion Laboratory (HPCL) to conduct corrosion tests on turbine materials by burning ASL/AXL crude continuously for 2,000 hours. Why it matters: This partnership could reduce reliance on natural gas and offer an economically viable alternative fuel source, bolstering energy security in Saudi Arabia and potentially influencing turbine technology worldwide.
KAUST hosted Saudi Arabia's first National Hackathon of Energy, in partnership with the Saudi Electricity Company's Innovation Energy Incubator. Innovators collaborated to find technical solutions for the Kingdom's energy challenges. Three projects were honored: AI-HUB for cybersecurity, a smart circuit breaker, and 'Amn Al-Kafa’at,' a fire extinguisher system. Why it matters: This hackathon highlights the growing focus on using AI and technology to address energy challenges in Saudi Arabia, with KAUST playing a central role in fostering innovation.
KAUST and the Saudi Electricity Company (SEC) collaborated to reduce non-technical losses in the Saudi power sector using machine learning. KAUST Visualization Core Lab (KVL) developed models using five years of SEC billing data from the Riyadh area to predict electricity usage and detect anomalous billing transactions. SEC estimates it could recover at least 73,000,000 SAR in lost revenue by correcting anomalies identified by KAUST models. Why it matters: This partnership demonstrates the potential of AI to address inefficiencies and fraud in critical infrastructure sectors in Saudi Arabia.
KAUST Professor J. Carlos Santamarina is researching solutions to the global energy challenge, focusing on sustainable energy production while reducing CO2 emissions. He notes the increasing energy demand due to population growth and the limitations of current energy sources. Santamarina emphasizes the need for fuel-producing countries to participate in carbon capture and storage to meet carbon targets. Why it matters: This research contributes to addressing critical sustainability challenges in the region, especially in oil-producing countries like Saudi Arabia.
A KAUST article discusses the future of energy, highlighting the role of hydrocarbon fuels and the need for sustainable practices. Professor Tadeusz W. Patzek's paper emphasizes finding sustainable bridges until alternative energy sources become viable. The article contrasts optimistic and pessimistic views on energy sustainability, drawing parallels to the whale oil industry. Why it matters: The piece highlights the tension between continued reliance on fossil fuels and the urgent need for alternative energy sources and reduced consumption in the GCC region and globally.
MBZUAI's Qirong Ho and colleagues are developing an Artificial Intelligence Operating System (AIOS) for decarbonization, aiming to reduce energy waste in AI development. The AIOS focuses on improving communication efficiency between machines during AI model training, as inefficient communication leads to prolonged tasks and increased energy consumption. This system addresses the high computing power demands of large language models like ChatGPT and LLaMA-2. Why it matters: By optimizing energy usage in AI development, the AIOS could significantly reduce the carbon footprint of AI technologies in the region and globally.
KAUST hosted the KAUST Research Conference: Advances in Well Construction with Focus on Near-Wellbore Physics and Chemistry from November 7 to 9. The conference was co-chaired by Eric van Oort, a professor at UT Austin, and Tadeusz Patzek, director of the University’s Upstream Petroleum Engineering Research Center. Attendees included professors from the University of Queensland and UT Austin, and directors from GenesisRTS and Labyrinth Consulting Services, Inc. Why it matters: The conference facilitates international collaboration on advancements in petroleum engineering and well construction technologies, which are strategically important for Saudi Arabia.
This paper introduces an AI-driven decision support system for green hydrogen investment in Oman, specifically for the Duqm R3 auction. The system uses publicly available meteorological data to predict maintenance pressure on hydrogen infrastructure, creating a Maintenance Pressure Index (MPI). This tool supports regulatory oversight and operational decision-making by enabling temporal benchmarking against performance claims.