Optimization of Chlorine Injection Dosage in Water Distribution Networks Using a Genetic Algorithm

Water supply management, both in terms of quality and quantity, is facing serious problems due to growing municipal, industrial, and agricultural demands. Disinfection and bacterial removal from water by chemicaland/or physical treatment processes are the minimum requirements in any water distribution system. Disinfection can be performed in a variety of ways, the most common and cheapest being chlorination. Selecting proper injection points in the network and determining chlorine dosages are basic considerations in maintaining chlorine residual at standard levels at nodes across the network and minimizing operation costs. Minimum chlorine residual levels must be determined so as to prevent bacterial growth in water and maximum levels should not be exceeded in order to avoid customer complaints about taste and smell or to inhibit the formation of potentially toxic by-products. Improper water quality management with respect to chlorine residual levels has at times led to serious problems to occur in many parts of the world. In this paper, the EPANET software package capable of water quality and hydraulic simulations has been integrated with a Genetic Algorithm nonlinear optimization model to derive a combined model for optimizing chlorine dosage. Two real-life examples adapted from water distribution networks have been used to verify the efficiency of the proposed model in determining optimal chlorine dosage. The results indicate that chlorine residual at nodes in water supply networks can be maintained at standard levels if chlorine injection is accomplished in more than one reservoir and if these reservoirs as injection points are properly selected. Application of the model led to a decrease in the total chlorine consumption and to an increase in the number of nodes where chlorine residual met the standard.