Research on Parameter Estimation of Water Quality Models Based on Genetic Algorithm
Chlorine is the most common disinfectant to maintain the quality of drinking water in the water distribution networks.However,the concentration of chlorine is strictly restricted,which should be adequate to remove pathogens but not produce excessive disinfectant by-products.Hence real-time water quality model is very important for keeping the optimal target residual chlorine concentrations in the water distribution networks.The accuracy of water quality model can only be retained by regular calibration and validation utilizing field measured chlorine concentration data.In this research,a genetic algorithm is implemented to automatically search for the optimal value of chlorine decay parameters.An investigation of the impact of pipe grouping on the calibration performance is conducted.Further-more,the ability of genetic algorithm method in dealing with data uncertainties is tested to validate its robustness.
water distribution networkresidual chlorine decaywater quality model calibrationgenetic algorithm
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