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Micro hydropower generators (micro turbines), are used to recover excess energy from hydraulic systems and these applications have important potential in renewable energy production. One of the most viable environments for the use of micro turbines is the water distribution network where, by design, there is always excess energy since minimum pressures are to be maintained throughout the system, and the system is designed to meet future water supply needs of a planning period. Under these circumstances, maintaining the target pressures is not an easy task due to the increasing complexity of the water distribution network to supply future demands. As a result, pressures at several locations of the network tend to be higher than the required minimum pressures. In this paper, we outline a methodology to recover this excess energy using smart operation management and the best placement of micro turbines in the system. In this approach, the best micro turbine locations and their operation schedule is determined to recover as much available excess energy as possible from the water distribution network while satisfying the current demand for water supply and pressure. Genetic algorithms (GAs) are used to obtain optimal solutions and a “smart seeding” approach is developed to improve the performance of the GA. The Dover Township pump-driven water distribution system in New Jersey, United States of America (USA) was selected as the study area to test the proposed methodology. This pump-driven network was also converted into a hypothetical gravity-driven network to observe the differences between the energy recovery potential of the pump-driven and gravity-driven systems. The performance of the energy recovery system was evaluated by calculating the equivalent number of average American homes that can be fed by the energy produced and the resulting carbon-dioxide emission reductions that may be achieved. The results show that this approach is an effective tool for applications in renewable energy production in water distribution systems for small towns such as Dover Township. It is expected that, for larger water distribution systems with high energy usage, the energy recovery potential will be much higher.

Optimal Energy Recovery from Water Distribution Systems Using Smart Operation Scheduling