Chlorine demand as a disinfectant for water utility impacts on unintended energy consumption from electrolysis manufacture; thus, diminishing the chlorine consumption also reduces the environmental impact and energy consumption. Problems of disinfectant distribution and uniformity in Water Distribution Networks (WDN) are associated with the exponential urban growth and the physical and biochemical difficulties within the network. This study optimizes Chlorine Booster Stations (CBS) location on a network with two main objectives; (1) to deliver minimal Free Residual Chlorine (FRC) throughout all demand nodes according to country regulations, and (2) to reduce day chlorine mass concentration supplied in the system by applying an hour time pattern in CBS, consequently associated economic, energy and environmental impacts complying with regulatory standards. The application is demonstrated on a real-world WDN modeled from Guanajuato, Mexico. The resulting optimal location and disinfectant dosage schedule in CBS provided insights on maintaining disinfectant residuals throughout all the WDN to prevent health issues and diminishing chlorine consumption.

This research proposes a methodology with multi-objective optimization for the placement of Pumps operating As Turbines (PATs), energizing street lighting, devices for monitoring the water network, and charging stations for small electric vehicles such as bikes and scooters. This methodology helps to find the most profitable project for benefiting life quality and energy recovery through pumps operating as turbines, replacing virtual pressure reduction valves to locate the best point for decreasing pressure. PATs are selected by maximizing power recovery and minimizing pressure in the system as well as maximizing recoverable energy. Benefits analyzed include the reduction of carbon dioxide emissions and fuel use, as well as the saving of electricity consumption and benefiting socio-economic impact with street lighting, monitoring, and charging station. It was considered that each PAT proposed by the methodology will supply a street light pole, a station for monitoring the water network, and a charging station; under these established conditions, the return on investment is up to 1.07 at 12 years, with a power generation of 60 kWh per day.

La concentración de cloro como desinfectante suministrado a la red de distribución de agua decae con el paso del tiempo debido a su interacción con microorganismos, metales y otras sustancias presentes en el agua. Los programas de computadora, como Epanet, se utilizan para simular el comportamiento hidráulico y la calidad del agua en las redes de distribución; con su ayuda se pueden representar modificaciones físicas y operativas en un modelo numérico para conocer el nuevo comportamiento sin comprometer la calidad del servicio. La calibración del modelo de cloro como desinfectante consiste en tomar como referencia la concentración en varios puntos de la red y ajustar los coeficientes de decaimiento en el modelo hasta lograr que las concentraciones simuladas coincidan con las medidas. En el presente artículo se muestra la automatización de este proceso haciendo uso de la técnica heurística algoritmos genéticos y la Toolkit de EPANET con MATLAB (2016). El proceso de calibración se realiza en un sector de la red de distribución de la ciudad de Guanajuato, obteniendo una correlación de 0.816 con un error promedio absoluto de 0.08 mg/l entre las concentraciones modeladas y medidas; y que como resultado permitirá conocer la concentración del cloro en diversos puntos de la red, asegurándose de brindar un servicio de calidad durante el abastecimiento.

EPANET can be used to simulate quality on water distribution networks. The EPANET model considers that the mixing on cross junctions of pipes is complete, including the cases of two contiguous inlets and two contiguous outlets. The output concentration of this model is the same value on the two outlets. This research proposes a code to generate an INP file for EPANET but with an incomplete mixing scenario in the crossings. The cross junctions are identified, and their hydraulic and concentration conditions are analyzed for each quality time step. Bypass pipes are included in the model to remove concentrations generated by the complete mixing model, preserve continuity in water quality and ensure the correct allocation of concentration. The concentration at the outlets is obtained by a system of polynomial equations representing the incomplete mixing model as a function of the hydraulic and concentration at the junction inlets. The outlets’ concentrations are incorporated by setpoint boosters. Validations are described to demonstrate the achievement of the new code. An average relative concentration difference of up to 14% is obtained in networks with different scenarios for the two mixing models.