Estimation of Chlorine Concentration in Water Distribution Systems Based on a Genetic Algorithm

This paper proposes a methodology based on a genetic algorithms (GA) to calibrate the parameters of a chlorine decay model in a water distribution system (WDS). The proposed methodology first contemplates that a GA is implemented using historical measurements of chlorine concentration at some sensed nodes to calibrate the unknown values corresponding to both the bulk and wall reaction coefficients. Once both parameters are estimated, the optimal-fit chlorine decay model is used to predict the decay of chlorine concentration in the water at each node for any concentration input at the pumping station. Then, a second GA-based algorithm is implemented to obtain the minimal chlorine concentration needed at the input to ensure that every node in the system meets the official normativity requirements for free chlorine in a WDS. The proposed methodology performed satisfactorily for a WDS simulated in EPANET with a GA implemented in MATLAB, both for the estimation of the reaction coefficients and the optimization of the required chlorine concentration at the input. Simulation results illustrate the performance of the proposed algorithm.

Automated summary

This paper proposes a methodology using genetic algorithms (GA) to calibrate the parameters of a chlorine decay model in a water distribution system (WDS). The methodology first uses historical measurements to calibrate the reaction coefficients and then predicts the chlorine concentration decay at each node using the optimal-fit decay model. A second GA-based algorithm is used to optimize the required chlorine concentration at the input to meet normativity requirements. The proposed methodology performed well in the simulated WDS.