Optimizing Locations for Chlorine Booster Stations in Small Water Distribution Networks

Islam, Nilufar; Sadiq, Rehan; Rodriguez, Manuel J.

doi:10.1061/(asce)wr.1943-5452.0000759

Cited by 23 publications

(10 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, multi-objective optimization was also applied to solve the WQC problem, where Prasad et al [14] used a multi-objective genetic algorithm (NSGA-II) to minimize the total disinfectant dose and simultaneously maximize the water demand within specified residual limits. A comprehensive review of the literature on the optimization of booster chlorination systems can be found in the recent works by Islam et al [15], and Mala-Jetmarova et al [16].…”

Section: A Literature Reviewmentioning

confidence: 99%

How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control

Wang,

Taha,

Abokifa

2020

Preprint

View full text Add to dashboard Cite

Real-time water quality control (WQC) in water distribution networks (WDN), the problem of regulating disinfectant levels, is challenging due to lack of (i) a proper control-oriented modeling considering complicated components (junctions, reservoirs, tanks, pipes, pumps, and valves) for water quality modeling and (ii) a corresponding scalable control algorithm that performs realtime water quality regulation. In this paper, we solve the WQC problem by (a) proposing a novel state-space representation of the WQC problem that provides explicit relationship between inputs (chlorine dosage at booster stations) and states/outputs (chlorine concentrations in the entire network) and (b) designing a highly scalable model predictive control (MPC) algorithm that showcases fast response time and resilience against some sources of uncertainty.

show abstract

Section: A Literature Reviewmentioning

confidence: 99%

How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control

Wang,

Taha,

Abokifa

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…min n P P ≥ (38) …where Q ⊆ R D is the decision space (that is the set of all commercially available pipe diameters); c is the cost function associated with the problem; ΔPn is the head deficit at each network node; and D, N, and L are the number of links to be designed (decision variables), the number of nodes, and the number of loops in the network, respectively. Equation 35describes the conservation of mass while Equation 36represents the conservation of energy, where the head loss along each pipe is given by Equation 37, with CW being the Hazen-Williams loss coefficient.…”

Section: Cosmentioning

confidence: 99%

Surveying the Optimization Problems of Water Distribution Networks

Ruiz-Vanoye¹,

Barrera-Cámara²,

Díaz-Parra³

et al. 2018

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

Pipelines [1] transport such resources as water, petroleum products, telecommunications, chemicals, natural gas, sewage, beer, biofuels (ethanol and biobutanol), and hydrogen. The Locations are residential and commercial areas, treatment plants, processing facilities, gas stations, pumping stations, terminals, tanks, storage facilities, partial delivery stations, inlet stations, injection stations, block valve stations, regulator stations, final delivery stations, floors (levels, decks) of a building, vessels, or other structures [1]. Water transportation problems (WTP) is a generic name given to a whole class of problems in which water transportation is necessary by pipelines or other means. Water distribution networks carry resources (drinking water, purified water, deionized water, distilled water, hard water, heavy water, soft water, tritiated water) to such locations as water storage facilities by pipelines and ducts. A water distribution network is a hydraulic infrastructure that is part of the water supply system composed of a set of pipes, hydraulic devices (pumps, pressure-reducing valves, etc.), and reservoirs [2]. The problems that arise in the distribution of water are usually the following: distribution of cities lack adequate modernization and maintenance, which cause loss of water resources, and poor distribution of water as a consequence causes the water to run through more miles to reach its destination. Traditionally networks of water

show abstract

“…Usually, the studies set scheduling patterns by groups of six hours [32]; thus, the operation of each CBS is described by four separate constant mass injections along 24 h [32,[36][37][38]. Some research on CBS focuses on mathematical models to propose the optimal location and injection dosage in the WDS, and others use Artificial Intelligence (AI) [39]. Using AI and informatics allows the simulation of several scenarios before construction investment of the CBS, thus saving money and time in project development [40].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

View full text Add to dashboard Cite

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.

show abstract

Optimizing Locations for Chlorine Booster Stations in Small Water Distribution Networks

Cited by 23 publications

References 42 publications

How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control

How Effective is Model Predictive Control in Real-Time Water Quality Regulation? State-Space Modeling and Scalable Control

Surveying the Optimization Problems of Water Distribution Networks

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

Contact Info

Product

Resources

About