Interactive nonlinear multiobjective optimal design of water distribution systems using Pareto navigator technique

Sustainable water distribution systems comprise complex combinations of critical components that are simultaneously optimized. The trade-offs and interactions that exist among these components, however, will introduce difficult challenges to optimization algorithms. In this paper, a multiobjective optimization formulation is proposed to scrupulously manage the demand, leakage, and age of water, as well as energy consumption of water distribution systems. Pareto navigator approach, a learning-oriented algorithm, is used to attain the final Pareto optimal solution for water network. The optimal power consumption, leakage, demand, and water age are used as inputs to the upper level energy resource allocation to optimize the energy demand and operational cost of integrated water–energy system. Numerical results show 76.6%, 95.4%, 13.14%, and 27.4% reduction in leakage, water age, water usage, and energy consumption of water network over 24 h, respectively, while the daily cost of electricity generation reduces by 3.7%. The energy system is designed based on isolated energy units, also known as microgrids, with minimum dependency on the fossil-fuel-based power plants. As such, the proposed multiobjective bi-level optimization model will also improve the carbon footprint of water distribution systems and their impact on climate change.