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

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5806
Author(s):  
Joseph D. Pineda Sandoval ◽  
Bruno Melo Brentan ◽  
Gustavo Meirelles Lima ◽  
Daniel Hernández Cervantes ◽  
Daniel A. García Cervantes ◽  
...  

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.

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1999
Author(s):  
Malvin S. Marlim ◽  
Doosun Kang

Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.


2011 ◽  
Vol 11 (4-5) ◽  
pp. 731-747 ◽  
Author(s):  
MASSIMILIANO CATTAFI ◽  
MARCO GAVANELLI ◽  
MADDALENA NONATO ◽  
STEFANO ALVISI ◽  
MARCO FRANCHINI

AbstractThis paper presents a new application of logic programming to a real-life problem in hydraulic engineering. The work is developed as a collaboration of computer scientists and hydraulic engineers, and applies Constraint Logic Programming to solve a hard combinatorial problem. This application deals with one aspect of the design of a water distribution network, i.e., the valve isolation system design. We take the formulation of the problem by Giustolisi and Savić (2008 Optimal design of isolation valve system for water distribution networks. InProceedings of the 10th Annual Water Distribution Systems Analysis Conference WDSA2008, J. Van Zyl, A. Ilemobade, and H. Jacobs, Eds.) and show how, thanks to constraint propagation, we can get better solutions than the best solution known in the literature for the Apulian distribution network. We believe that the area of the so-calledhydroinformaticscan benefit from the techniques developed in Constraint Logic Programming and possibly from other areas of logic programming, such as Answer Set Programming.


Entropy ◽  
2018 ◽  
Vol 20 (8) ◽  
pp. 576 ◽  
Author(s):  
Do Yoo ◽  
Dong Chang ◽  
Yang Song ◽  
Jung Lee

This study proposed a pressure driven entropy method (PDEM) that determines a priority order of pressure gauge locations, which enables the impact of abnormal condition (e.g., pipe failures) to be quantitatively identified in water distribution networks (WDNs). The method developed utilizes the entropy method from information theory and pressure driven analysis (PDA), which is the latest hydraulic analysis method. The conventional hydraulic approach has problems in determining the locations of pressure gauges, attributable to unrealistic results under abnormal conditions (e.g., negative pressure). The proposed method was applied to two benchmark pipe networks and one real pipe network. The priority order for optimal locations was produced, and the result was compared to existing approach. The results of the conventional method show that the pressure reduction difference of each node became so excessive, which resulted in a distorted distribution. However, with the method developed, which considers the connectivity of a system and the influence among nodes based on PDA and entropy method results, pressure gauges can be more realistically and reasonably located.


2018 ◽  
Author(s):  
Karel van Laarhoven ◽  
Ina Vertommen ◽  
Peter van Thienen

Abstract. Genetic algorithms can be a powerful tool for the automated design of optimal drinking water distribution networks. Fast convergence of such algorithms is a crucial factor for successful practical implementation at the drinking water utility level. In this technical note, we therefore investigate the performance of a suite of genetic variators that was tailored to the optimisation of a least-cost network design. Different combinations of the variators are tested in terms of convergence rate and the robustness of the results during optimisation of the real world drinking water distribution network of Sittard, the Netherlands. The variator configurations that reproducibly reach the furthest convergence after 105 function evaluations are reported. In the future these may aid in dealing with the computational challenges of optimizing real world networks.


2021 ◽  
Vol 11 (23) ◽  
pp. 11525
Author(s):  
Oscar Danilo Montoya ◽  
Luis Fernando Grisales-Noreña ◽  
Lázaro Alvarado-Barrios ◽  
Andres Arias-Londoño ◽  
Cesar Álvarez-Arroyo

This research addresses the problem of the optimal placement and sizing of (PV) sources in medium voltage distribution grids through the application of the recently developed Newton metaheuristic optimization algorithm (NMA). The studied problem is formulated through a mixed-integer nonlinear programming model where the binary variables regard the installation of a PV source in a particular node, and the continuous variables are associated with power generations as well as the voltage magnitudes and angles, among others. To improve the performance of the NMA, we propose the implementation of a discrete–continuous codification where the discrete component deals with the location problem and the continuous component works with the sizing problem of the PV sources. The main advantage of the NMA is that it works based on the first and second derivatives of the fitness function considering an evolution formula that contains its current solution (xit) and the best current solution (xbest), where the former one allows location exploitation and the latter allows the global exploration of the solution space. To evaluate the fitness function and its derivatives, the successive approximation power flow method was implemented, which became the proposed solution strategy in a master–slave optimizer, where the master stage is governed by the NMA and the slave stage corresponds to the power flow method. Numerical results in the IEEE 34- and IEEE 85-bus systems show the effectiveness of the proposed optimization approach to minimize the total annual operative costs of the network when compared to the classical Chu and Beasley genetic algorithm and the MINLP solvers available in the general algebraic modeling system with reductions of 26.89% and 27.60% for each test feeder with respect to the benchmark cases.


2018 ◽  
Vol 19 (3) ◽  
pp. 846-854 ◽  
Author(s):  
M. A. Pardo ◽  
J. Valdes-Abellan

Abstract Traditional methods for prioritizing the renewal of water are based on heuristic models, such as the number of breaks per length, rule-of-thumb, and records held by the water utility companies. Efficient management of water distribution networks involves factoring in water and energy losses as the key criteria for planning pipe renewal. Prioritizing the replacement of a pipe according to the highest value of unit headloss due to ageing does not consider the impact on water and energy consumption for the whole network. Thus, this paper proposes a methodology to prioritize pipe replacement according to water and energy savings per monetary unit invested – economic prioritization. This renewal plan shows different results if comparing with replacing pipelines with regard to age and it requires calculating water and energy audits of the water distribution networks. Moreover, the required time to recover the investment performed needs to be calculated. The methodology proposed in this work is compared with the unit headloss criterion used in a real water-pressurized network. The results demonstrate that using the unit headloss criterion neither water, energy nor the investment is optimized. Significant water and energy savings are not fully exploited.


Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1154
Author(s):  
Chao-Chih Lin ◽  
Hund-Der Yeh

This research introduces an inverse transient-based optimization approach to automatically detect potential faults, such as leaks, partial blockages, and distributed deteriorations, within pipelines or a water distribution network (WDN). The optimization approach is named the Pipeline Examination Ordinal Symbiotic Organism Search (PEOS). A modified steady hydraulic model considering the effects of pipe aging within a system is used to determine the steady nodal heads and piping flow rates. After applying a transient excitation, the transient behaviors in the system are analyzed using the method of characteristics (MOC). A preliminary screening mechanism is adopted to sift the initial organisms (solutions) to perform better to reduce most of the unnecessary calculations caused by incorrect solutions within the PEOS framework. Further, a symbiotic organism search (SOS) imitates symbiotic relationship strategies to move organisms toward the current optimal organism and eliminate the worst ones. Two experiments on leak and blockage detection in a single pipeline that have been presented in the literature were used to verify the applicability of the proposed approach. Two hypothetical WDNs, including a small-scale and large-scale system, were considered to validate the efficiency, accuracy, and robustness of the proposed approach. The simulation results indicated that the proposed approach obtained more reliable and efficient optimal results than other algorithms did. We believe the proposed fault detection approach is a promising technique in detecting faults in field applications.


Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 493 ◽  
Author(s):  
Jorge Francés-Chust ◽  
Bruno M. Brentan ◽  
Silvia Carpitella ◽  
Joaquín Izquierdo ◽  
Idel Montalvo

Nowadays, optimal sensor placement (OSP) for leakage detection in water distribution networks is a lively field of research, and a challenge for water utilities in terms of network control, management, and maintenance. How many sensors to install and where to install them are crucial decisions to make for those utilities to reach a trade-off between efficiency and economy. In this paper, we address the where-to-install-them part of the OSP through the following elements: nodes’ sensitivity to leakage, uncertainty of information, and redundancy through conditional entropy maximisation. We evaluate relationships among candidate sensors in a network to get a picture of the mutual influence among the nodes. This analysis is performed within a multi-criteria decision-making approach: specifically, a herein proposed variant of DEMATEL, which uses fuzzy logic and builds comparison matrices derived from information obtained through leakage simulations of the network. We apply the proposal first to a toy example to show how the approach works, and then to a real-world case study.


Proceedings ◽  
2018 ◽  
Vol 2 (23) ◽  
pp. 1440 ◽  
Author(s):  
Jorge García Morillo ◽  
Juan A. Rodríguez Díaz ◽  
Miguel Crespo ◽  
Aonghus McNabola

In Spain and other countries, open channel distribution networks have been replaced by on demand-pressurized networks to improve the water-use efficiency of the water distribution systems, but at the same time the energy requirements have dramatically risen. Under this scenario, methodologies to reduce the energy consumption are critical such as: irrigation network sectoring, critical hydrant detection, improving the efficiency of the pumping system and the irrigation system, or introducing solar energy for water supply. But once these measures are undertaken, the recovery of the energy inherent in excess pressure in the network should be investigated. Hydropower energy recovery in irrigation is still largely unexplored and requires further investigation and demonstration. All of these methodologies should be considered as useful tools for both, the reduction of energy consumption and the recovery of the excess energy in pressurized irrigation networks. To accomplish this, the REDAWN project (Reducing Energy Dependency in Atlantic Area Water Networks) aims to improve the energy efficiency of water networks through the installation of innovative micro-hydropower (MHP) technology. This technology will recover wasted energy in existing pipe networks across irrigation, public water supply, process industry, and waste-water network settings.


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