Optimal Scheduling of Booster Chlorination with Immune Algorithm

This paper describes the methodology and application of an immune algorithm (IA) scheme tailor-made for the EPANET for simultaneously optimizing the injection rates and scheduling of chlorine booster stations under the unsteady state of a water distribution network system (WDNS). The objective of this study is to initiate a total chlorination dose to satisfy the minimum and maximum required chlorine residual at every demand node in a WDNS while minimizing the chlorine consumption as much as possible. The decision variables are the scheduling of the mass injection rate at the booster node in the WDNS segments. The evaluation results confirm the potential of IA in solving the scheduling of booster disinfection optimization problems.