Abstract:
In numerous locations of bulk water supply/distribution systems, energy is dissipated by
pressure-reducing devices, whereas it could be recovered by means of turbines or pumps as turbines.
These pipe systems, owned and operated by municipalities, water utilities, large water-consuming
industries, and mines, could be used as a source of renewable sustainable energy. However, the
exploitation of these systems presents several issues related to the complexity of the operational
optimization of the hydropower generation facilities and to the potential negative impact on the
reliability of the system itself. We have developed a novel procedure to optimize the energy generation
in such a conduit system by assessing the interrelationship of storage volumes, demand patterns,
operating cycles, and electricity tariff structures. The procedure is a multi-objective genetic algorithm
designed to provide a solution to maximize electricity generation and thus revenue and to minimize
the risk involved in supplying the demand. A Pareto-optimal trade-off curve is set up, indicating the
potential benefit (revenue) versus the reliability index (supply security). The results indicate that a
Pareto-optimal trade-off curve was generated from which a solution could be selected which would
improve the weekly revenue by up to 7.5%, while still providing a reliable water supply system.
