The optimization of pump operations has the potential to reduce operational costs, while still maintaining the high level of reliability required of water distribution systems. The hydraulic software EPANET2 toolkit has been frequently linked to evolutionary algorithms for this purpose; however, only time-based controls and simple controls based on one single condition, e.g., the tank level, could be automatically changed during the optimization. This paper introduces a modification to the original EPANET2 toolkit library, so that the operation of pumps can be optimized taking into account simultaneously several conditions (e.g., the time of the day and the tank level). A problem in the original toolkit associated with computing pump energy and costs using rule-based controls has also been solved. The new ETTAR toolkit has been tested on a case study, in which a genetic algorithm has been used to optimize different types of controls. Results show that it is possible to find more cost-effective solutions compared to simple controls and, although with longer computational times, let the algorithm create the entire pump control rule set. The robustness of the optimized controls found has also been tested.
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