Shaaban, MostafaAlshamsi, Aisha Rashid2025-04-142025-04-142024-0535.232-2024.72https://hdl.handle.net/11073/26003A Master of Science thesis in Electrical Engineering by Aisha Rashid Alshamsi entitled, “A Real-Time Energy Management System Across Diverse Energy Sectors in Smart Cities”, submitted in May 2024. Thesis advisor is Dr. Mostafa Shaaban. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The population growth and economic expansion have led to an unprecedented demand for energy, water, and transportation. This increased demand is contributing to the increase of greenhouse gas (GHG) emissions and intensifying the climate crisis. As a result, governments are strategically pursuing carbon neutrality by introducing the use of renewable energy resources (RESs) and electrifying various end-uses, such as electric vehicles, in power systems. Further, the adoption of advanced water treatment methods, with a particular emphasis on the energy-intensive desalination method, the seawater reverse osmosis (SWRO), becomes essential, especially in arid regions where conventional water sources are scarce. Integrating various energy sectors like SWRO systems and EV charging stations, and the existing electric power system presents significant challenges, primarily because the original design of the system did not accommodate these technologies. Consequently, the concept of an energy management system has emerged as an effective approach to bridging the gap between the different energy sectors. In this thesis, a new real-time framework is presented and tested for concurrently optimizing the three energy sectors as one interdependent model. The proposed model is a mixed-integer nonlinear programming model implemented within the GAMS optimization environment and is tested using the modified IEEE RTS 24-bus test system. The proposed approach takes into account the technical constraints of both the electric, water, and transportation systems, ensuring the optimization of their operation without compromising their technical limitations and the delivery of the services to customers. Several case studies are presented, each employing different optimization strategies. The results highlight the potential of real-time co-optimization in enhancing system flexibility and reducing costs. Specifically, it demonstrates a $73,000 or 12.7% reduction in operating costs for the co-optimized energy-water-transportation system.en-USElectric vehiclesEnergy managementDesalinationMINLPOptimizationRolling horizonSeawater reverse osmosisSolar PVThesis