Optimal use of chlorine in water distribution networks based on specific locations of booster chlorination: analyzing conditions in Mexico

Cervantes, Daniel Hernández; Rodríguez, José de Jesús Mora; Delgado-Galván, Xitlali; Medel, Josefina Ortiz; Magaña, Martín Rubén Jiménez

doi:10.2166/ws.2015.161

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…GA represents a feasible model since it explores the problem without needing a complete mathematical model. GA's has been deeply studied in hydraulic issues [43][44][45][46] even nowadays, as well as the optimal use of chlorine applying CBS [54].…”

Section: Genetic Algorithms (Ga)mentioning

confidence: 99%

Optimal Placement and Operation of Chlorine Booster Stations: A Multi-Level Optimization Approach

et al. 2021

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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.

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Section: Genetic Algorithms (Ga)mentioning

confidence: 99%

Optimal Placement and Operation of Chlorine Booster Stations: A Multi-Level Optimization Approach

et al. 2021

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Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches

Zounemat‐Kermani

Ramezani-Charmahineh

Adamowski

et al. 2018

Environ Monit Assess

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Chlorination, the basic treatment utilized for drinking water sources, is widely used for water disinfection and pathogen elimination in water distribution networks. Thereafter, the proper prediction of chlorine consumption is of great importance in water distribution network performance. In this respect, data mining techniques-which have the ability to discover the relationship between dependent variable(s) and independent variables-can be considered as alternative approaches in comparison to conventional methods (e.g., numerical methods). This study examines the applicability of three key methods, based on the data mining approach, for predicting chlorine levels in four water distribution networks. ANNs (artificial neural networks, including the multi-layer perceptron neural network, MLPNN, and radial basis function neural network, RBFNN), SVM (support vector machine), and CART (classification and regression tree) methods were used to estimate the concentration of residual chlorine in distribution networks for three villages in Kerman Province, Iran. Produced water (flow), chlorine consumption, and residual chlorine were collected daily for 3 years. An assessment of the studied models using several statistical criteria (NSC, RMSE, R, and SEP) indicated that, in general, MLPNN has the greatest capability for predicting chlorine levels followed by CART, SVM, and RBF-ANN. Weaker performance of the data-driven methods in the water distribution networks, in some cases, could be attributed to improper chlorination management rather than the methods' capability.

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Calibración de modelo de cloro mediante algoritmos genéticos en red de agua potable de Guanajuato

García-Cervantes,

Pineda-Sandoval,

Hernández-Cervantes

et al. 2024

Tecnol. cienc. agua

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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.

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Optimal use of chlorine in water distribution networks based on specific locations of booster chlorination: analyzing conditions in Mexico

Cited by 5 publications

References 14 publications

Optimal Placement and Operation of Chlorine Booster Stations: A Multi-Level Optimization Approach

Optimal Placement and Operation of Chlorine Booster Stations: A Multi-Level Optimization Approach

Investigating the management performance of disinfection analysis of water distribution networks using data mining approaches

Calibración de modelo de cloro mediante algoritmos genéticos en red de agua potable de Guanajuato

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