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Reliance on water production by desalination as a solution to water scarcity is growing worldwide. High energy demands of seawater desalination raise new challenges for both water and energy management and highlight the importance of understanding the operational dependencies of the water sector on energy supplies. This study provides an in-depth analysis of the impact of the water-energy nexus in a desalination-based water sector, using Israel as a case study. Being large energy consumers, desalination plants are part of the Electricity Load Shedding Program (ELSP), which government energy regulators invoke in times of energy shortage. We focus on the interdependency between the two sectors as manifested at the time of ELSP utilization during an extreme heat wave. We show that energy shedding compensation is 6 to 14 times greater than the economic loss to the desalination plant from no water production, creating an obvious economic incentive to participate in ELSPs. However, this imbalance has a substantial negative impact on the water sector, which may compromise the level of service. Our evaluation concludes that the government authorities regulating water and energy need an official mechanism and policy for joint management strategies that can ensure economic efficiency and reduce the risk of power and water shortages during extreme events. 

Abstract Water distribution systems (WDSs) are critical infrastructure used to convey water from sources to consumers. The mathematical framework governing the distribution of flows and heads in extended period simulations of WDSs lends itself to application in a wide range of optimization problems. Applying the classical mixed integer linear programming (MILP) approach to model WDSs hydraulics within an optimization framework can contribute to higher solution accuracy with lower computational effort. However, adapting WDSs models to conform to a MILP formulation has proven challenging because of the intrinsic non‐linearity of system hydraulics and the complexity associated with modeling hydraulic devices that influence the state of the WDS. This paper introduces MILPNet, an adjustable framework for WDSs that can be used to build and solve an extensive array of MILP optimization problems. MILPNet includes constraints that represent the mass balance and energy conservation equations, hydraulic devices, control rules, and status checks. To conform to MILP structure, MILPNet employs piece‐wise linear approximation and integer programming. MILPNet was implemented and tested using Gurobi Python API. Modeling accuracy was shown to be comparable to EPANET, a public domain software for hydraulic modeling, and sensitivity analyses were conducted to examine the impacts of the modeling assumptions on the performance of MILPNet. Additionally, application of the framework was demonstrated using pump scheduling optimization examples in single and rolling horizon scenarios. Our results show that MILPNet can facilitate the construction and solution of optimization problems for a range of applications in WDSs operations.