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In recent decades, Saudi Arabia has experienced a significant surge in energy consumption as a result of population growth and economic expansion. This has presented utility companies with the formidable challenge of upgrading their facilities and expanding their capacity to keep pace with future energy demands. In order to address this issue, there is an urgent need to implement energy-saving solutions such as energy storage systems (ESSs) and renewable energy sources, which can help to reduce demand during peak hours. To ensure optimal use of ESSs, it is crucial to integrate a load forecasting model with the ESS in order to control charging and discharging rates and schedules. The irregular load profile is a particularly significant consumer of energy, consuming approximately 2.5 GWh annually at the cost of USD 3 billion in Saudi Arabia. In light of this, this paper develops a load forecasting model for the irregular load profile with a high degree of accuracy: achieving 95%. One of the key applications of this model is load peak shaving. Given the region's abundance of solar irradiation, the paper propose an integration of a solar PV system with a battery energy storage system (BESS) and analyzes various scenarios to determine the efficacy of the proposed approach. The results demonstrate significant savings when the proposed forecasting model is integrated with a BESS and PV system, with the potential to reduce monthly imported power by more than 22% during the summer season. [ABSTRACT FROM AUTHOR]

With the sharply growing complexity and rapid deployment of smart technologies in our modern society, risk-aware management and coordination in day-to-day operation of the interlinked critical infrastructures is urgently needed. In particular, the interconnected water and power systems (WaPS) are in need of joint and cooperative operation to maximize the economic benefits during normal operating conditions and resilience services during emergencies. While contingency analysis is used to assist the system operators in gaining knowledge of the system’s static security, such understanding is more challenging to achieve in the case of integrated WaPS. This article proposes a novel optimization model for under-emergency operation of the integrated WaPS, considering contingencies in both networks. In order to ensure the delivery of water demand, the proposed formulation considers the hydraulic constraints of the water networks, which is naturally a nonlinear model. The proposed nonlinear model is approximated using a piece-wise linearization approach to convert the optimization model into a mixed-integer linear programming formulation. The proposed analytics are applied to a modified IEEE 24-bus reliability test system that is jointly operated with two and three commercial-scale water networks. The proposed model is evaluated using various disaster severity levels (i.e., $N-k$ contingency scenarios) and verify the promising performance of the proposed integrated WaPS model when facing failures and threatening high impact low probability emergencies. [ABSTRACT FROM AUTHOR]