Supplying high-quality water at competitive cost is a major challenge for water utilities worldwide, especially with ever increasing water quality standards and energy prices. A number of pump scheduling methods for optimizing simultaneously water quality and energy cost have been developed already. However, none of these methods is ideal because of the complexity of water networks and the nonlinear behavior of water flow. In this research, a new optimization method named iterative extended lexicographic goal programming (iELGP) is developed to optimize energy cost and water quality (residual chlorine) in water networks with a mixture of fixed speed pumps (FSPs) and variable speed pumps (VSPs). Two different approaches were used to indirectly improve chlorine. The new method was tested on the C-Town water network and compared with the graph theory method from the literature. The results obtained show the ability of the iELGP method to optimize energy cost and water quality in water networks in a computationally very efficient manner. They also show that the iELGP method can identify lower energy cost pump schedules and do this faster than the comparison method. Using VSPs instead of FSPs improves the water quality and decreases the related energy and maintenance cost in water networks.
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Mohammed et al. (2019) studied this question.
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