scholarly journals Energy Optimization Using a Pump Scheduling Tool in Water Distribution Systems

2020 ◽  
Vol 8 (1) ◽  
pp. 112-123
Author(s):  
Karwan A. Muhammed ◽  
Raziyeh Farmani
Keyword(s):  
Optimization Algorithm ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Cost Effective ◽  
Water Systems ◽  
Water Levels ◽  
Pump Operation ◽  
Pump Scheduling ◽  
Scheduling Tool

Water distribution management system is a costly practice and with the growth of population, the needs for creating more cost-effective solutions are vital. This paper presents a tool for optimization of pump operation in water systems. The pump scheduling tool (PST) is a fully dynamic tool that can handle four different types of fixed speed pump schedule representations (on and off, time control, time-length control, and simple control [water levels in tanks]). The PST has been developed using Visual Basic programming language and has a linkage between the EPANET hydraulic solver with the GANetXL optimization algorithm. It has a user-friendly interface which allows the simulation of water systems based on (1) a hydraulic model (EPANET) input file, (2) an interactive interface which can be modified by the user, and (3) a pump operation schedule generated by the optimization algorithm. It also has the interface of dynamic results which automatically visualizes generated solutions. The capabilities of the PST have been demonstrated by application to two real case studies, Anytown water distribution system (WDS) and Richmond WDS as a real one in the United Kingdom. The results show that PST is able to generate high-quality practical solutions.

scholarly journals Optimal reconstruction of historical water supply to a distribution system: B. Applications

2004 ◽  
Vol 2 (3) ◽  
pp. 137-156 ◽  
Author(s):  
M. M. Aral ◽  
J. Guan ◽  
M. L. Maslia ◽  
J. B. Sautner ◽  
R. E. Gillig ◽  
...  
Keyword(s):  
New Jersey ◽  
Water Supply ◽  
Epidemiological Study ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Levels ◽  
Sensitivity Analyses ◽  
Toxic Substances

In a recently completed case-control epidemiological study, the New Jersey Department of Health and Senior Services (NJDHSS) with support from the Agency for Toxic Substances and Disease Registry (ATSDR) documented an association between prenatal exposure to a specific contaminated community water source and leukaemia in female children. An important and necessary step in the epidemiological study was the reconstruction of the historical water supply strategy of the water distribution system serving the Dover Township area, New Jersey. The sensitivity of solutions to: (1) pressure and pattern factor constraints, (2) allowable operational extremes of water levels in the storage tanks, and (3) the non-uniqueness of the water supply solution are analysed in detail. The computational results show that the proposed approach yields satisfactory results for the complete set of monthly simulations and sensitivity analyses, providing a consistent approach for identifying the historical water supply strategy of the water distribution system. Sensitivity analyses indicated that the alternative strategy obtained from the revised objective function and the variation of constraints did not yield significantly different water supply characteristics. The overall analysis demonstrates that the progressive optimality genetic algorithm (POGA) developed to solve the optimization problem is an effective and efficient algorithm for the reconstruction of water supply strategies in water distribution systems.

scholarly journals Trends in metering potable water

2018 ◽  
Vol 14 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Mario Maiolo ◽  
Manuela Carini ◽  
Gilda Capano ◽  
Daniela Pantusa ◽  
Marco Iusi
Keyword(s):  
Distribution System ◽  
Communication Systems ◽  
Distribution Systems ◽  
Water Distribution ◽  
Potable Water ◽  
Time Pressure ◽  
Data Communication ◽  
Cost Effective ◽  
Measuring Instruments ◽  
Water Meter

Abstract Sustainable management of drinking water distribution systems requires information on the operating status of system components to identify the best operational management measures. The ability to acquire information on tank levels, pipeline flow and real-time pressure offers an efficient and cost-effective management perspective, and enables wider monitoring, which can improve (physical) security as well. The technology of measuring instruments for hydrodynamic variables, used to monitor potable water systems, differs in their independence from electronic data acquisition components and ability to connect to remote data communication systems. Advanced water measurement infrastructure is characterized by the ability to capture data with measurable errors from anywhere in the system, without restrictions on communication type. This paper deals with the measurement of hydrodynamic parameters and a proposal for water meter classification. It includes analysis of the main water meter and data tele-acquisition infrastructure. Several selection criteria are evaluated with respect to their ability to support mathematical hydraulic models and expert systems for water distribution system management.

scholarly journals Optimal solving of the pump scheduling problem by using a Harmony Search optimization algorithm

2017 ◽  
Vol 19 (6) ◽  
pp. 879-889 ◽  
Author(s):  
F. De Paola ◽  
N. Fontana ◽  
M. Giugni ◽  
G. Marini ◽  
F. Pugliese
Keyword(s):  
Optimization Algorithm ◽  
Water Distribution ◽  
Heuristic Algorithms ◽  
Water Pressure ◽  
Harmony Search ◽  
Optimal Solution ◽  
Distribution Networks ◽  
Scheduling Problem ◽  
Pump Operation ◽  
Pump Scheduling

Abstract Pumps are installed in water distribution networks (WDNs) to ensure adequate service levels in the case of poor water pressure (e.g. because of low elevation of reservoirs or high head losses within the WDN). In such cases optimal pump scheduling is often required for the opportunity of significant energy saving. Optimizing the pump operation also allows a reduction in damage and maintenance times. Among the approaches available in the literature to solve the problem, meta-heuristic algorithms ensure reduced computational times, although they are not able to guarantee the optimal solution can be found. In this paper, a modified Harmony Search Multi-Objective optimization algorithm is developed to solve the pump scheduling problem in WDNs. The hydraulic solver EPANET 2.0 is coupled with the algorithm to assess the feasibility of the achieved solutions. Hydraulic constraints are introduced and penalties are set in case of violation of the set constraints to reduce the space of feasible solutions. Results show the high performances of the proposed approach for pumping optimization, guaranteeing optimal (or near optimal) solutions with short computational times.

The 1906 Earthquake Impacts on the San Francisco and Santa Clara Water Systems—What we Learned, and What we are doing about It

2006 ◽  
Vol 22 (2_suppl) ◽  
pp. 113-134 ◽  
Author(s):  
John Eidinger ◽  
Lota de Castro ◽  
Dennis Ma
Keyword(s):  
San Francisco ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Cost Effective ◽  
System Operator ◽  
Water Transmission ◽  
Pump Stations ◽  
Transmission And Distribution ◽  
The City

This paper describes what happened to San Francisco's water transmission and the city of Santa Clara's water distribution systems in the 1906 and the 1989 earthquakes. These two earthquakes showed that many of our existing transmission and distribution pipelines are susceptible to damage, and some of our older water treatment plants, tanks, and pump stations need to be upgraded. Accordingly, seismic upgrade programs are being undertaken to reduce the vulnerability of the regional water transmission and distribution systems. In developing a cost effective seismic upgrade program, both the transmission system operator (San Francisco Public Utilities Commission) (SFPUC) and distribution system operator (Santa Clara) consider what the weaknesses are of both systems, so that the maximum amount of seismic upgrade can be achieved at the lowest overall cost.

scholarly journals Multi-Objective and Multi-Criteria Analysis for Optimal Pump Scheduling in Water Systems

10.29007/vk44 ◽  
2018 ◽  
Author(s):  
Silvia Carpitella ◽  
Bruno Brentan ◽  
Idel Montalvo ◽  
Joaquín Izquierdo ◽  
Antonella Certa
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Pareto Front ◽  
Water Systems ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Operation Optimization ◽  
Multi Objective ◽  
Pump Scheduling ◽  
Multi Criteria Analysis

This contribution focuses on the problem of optimal pump scheduling, a fundamental element in pursuing operation optimization of water distribution systems. A combined approach of multi-objective optimization and multi-criteria analysis is herein suggested to first find the Pareto front of non-dominated solutions and then to rank them based on a set of weighted criteria. The Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve the multi-objective problem, while the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to achieve the final ranking.

scholarly journals Leakage Reduction in Water Distribution Systems with Efficient Placement and Control of Pressure Reducing Valves Using Soft Computing Techniques

2017 ◽  
Vol 7 (2) ◽  
pp. 1528-1534 ◽  
Author(s):  
A. Gupta ◽  
N. Bokde ◽  
D. Marathe ◽  
K. Kulat
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Reduction Rate ◽  
Cost Effective ◽  
Leakage Rate ◽  
Nsga Ii ◽  
Leakage Reduction ◽  
Soft Computing Techniques ◽  
And Control

Reduction of leakages in a water distribution system (WDS) is one of the major concerns of water industries. Leakages depend on pressure, hence installing pressure reducing valves (PRVs) in the water network is a successful techniques for reducing leakages. Determining the number of valves, their locations, and optimal control setting are the challenges faced. This paper presents a new algorithm-based rule for determining the location of valves in a WDS having a variable demand pattern, which results in more favorable optimization of PRV localization than that caused by previous techniques. A multiobjective genetic algorithm (NSGA-II) was used to determine the optimized control value of PRVs and to minimize the leakage rate in the WDS. Minimum required pressure was maintained at all nodes to avoid pressure deficiency at any node. Proposed methodology is applied in a benchmark WDS and after using PRVs, the average leakage rate was reduced by 6.05 l/s (20.64%), which is more favorable than the rate obtained with the existing techniques used for leakage control in the WDS. Compared with earlier studies, a lower number of PRVs was required for optimization, thus the proposed algorithm tends to provide a more cost-effective solution. In conclusion, the proposed algorithm leads to more favorable optimized localization and control of PRV with improved leakage reduction rate.

scholarly journals Application of genetic programming to modeling pipe failures in water distribution systems

2010 ◽  
Vol 13 (3) ◽  
pp. 419-428 ◽  
Author(s):  
Qiang Xu ◽  
Qiuwen Chen ◽  
Weifeng Li
Keyword(s):  
Genetic Programming ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Pipe Failure ◽  
Beijing City ◽  
Failure Data ◽  
Processing Strategies ◽  
Gis Data ◽  
Failure Models

The water loss from a water distribution system is a serious problem for many cities, which incurs enormous economic and social loss. However, the economic and human resource costs to exactly locate the leakage are extraordinarily high. Thus, reliable and robust pipe failure models are demanded to assess a pipe's propensity to fail. Beijing City was selected as the case study area and the pipe failure data for 19 years (1987–2005) were analyzed. Three different kinds of methods were applied to build pipe failure models. First, a statistical model was built, which discovered that the ages of leakage pipes followed the Weibull distribution. Then, two other models were developed using genetic programming (GP) with different data pre-processing strategies. The three models were compared thereafter and the best model was applied to assess the criticality of all the pipe segments of the entire water supply network in Beijing City based on GIS data.

scholarly journals A Head Formulation for the Steady-State Analysis of Water Distribution Systems Using an Explicit and Exact Expression of the Colebrook–White Equation

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1163
Author(s):  
Mengning Qiu ◽  
Avi Ostfeld
Keyword(s):  
Steady State ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Solution Method ◽  
Water Distribution System ◽  
Academic Research ◽  
Exact Expression ◽  
Contamination Source

Steady-state demand-driven water distribution system (WDS) solution is the bedrock for much research conducted in the field related to WDSs. WDSs are modeled using the Darcy–Weisbach equation with the Swamee–Jain equation. However, the Swamee–Jain equation approximates the Colebrook–White equation, errors of which are within 1% for ϵ/D∈[10−6,10−2] and Re∈[5000,108]. A formulation is presented for the solution of WDSs using the Colebrook–White equation. The correctness and efficacy of the head formulation have been demonstrated by applying it to six WDSs with the number of pipes ranges from 454 to 157,044 and the number of nodes ranges from 443 to 150,630. The addition of a physically and fundamentally more accurate WDS solution method can improve the quality of the results achieved in both academic research and industrial application, such as contamination source identification, water hammer analysis, WDS network calibration, sensor placement, and least-cost design and operation of WDSs.

scholarly journals Cyber—Physical Attack Detection in Water Distribution Systems with Temporal Graph Convolutional Neural Networks

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1247
Author(s):  
Lydia Tsiami ◽  
Christos Makropoulos
Keyword(s):  
Neural Networks ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Attack Detection ◽  
Convolutional Network ◽  
Irreversible Damage ◽  
Physical Attack ◽  
Temporal Graph ◽  
Graph Neural Networks

Prompt detection of cyber–physical attacks (CPAs) on a water distribution system (WDS) is critical to avoid irreversible damage to the network infrastructure and disruption of water services. However, the complex interdependencies of the water network’s components make CPA detection challenging. To better capture the spatiotemporal dimensions of these interdependencies, we represented the WDS as a mathematical graph and approached the problem by utilizing graph neural networks. We presented an online, one-stage, prediction-based algorithm that implements the temporal graph convolutional network and makes use of the Mahalanobis distance. The algorithm exhibited strong detection performance and was capable of localizing the targeted network components for several benchmark attacks. We suggested that an important property of the proposed algorithm was its explainability, which allowed the extraction of useful information about how the model works and as such it is a step towards the creation of trustworthy AI algorithms for water applications. Additional insights into metrics commonly used to rank algorithm performance were also presented and discussed.

scholarly journals Comparison of Searching Behaviour of Three Evolutionary Algorithms Applied to Water Distribution System Design Optimization

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 695 ◽  
Author(s):  
Weiwei Bi ◽  
Yihui Xu ◽  
Hongyu Wang
Keyword(s):  
Evolutionary Algorithms ◽  
Real Time ◽  
Distribution System ◽  
Optimization Design ◽  
Distribution Systems ◽  
Water Distribution ◽  
Optimal Solutions ◽  
Great Ability ◽  
Searching Behaviour ◽  
Run Time

Over the past few decades, various evolutionary algorithms (EAs) have been applied to the optimization design of water distribution systems (WDSs). An important research area is to compare the performance of these EAs, thereby offering guidance for the selection of the appropriate EAs for practical implementations. Such comparisons are mainly based on the final solution statistics and, hence, are unable to provide knowledge on how different EAs reach the final optimal solutions and why different EAs performed differently in identifying optimal solutions. To this end, this paper aims to compare the real-time searching behaviour of three widely used EAs, which are genetic algorithms (GAs), the differential evolution (DE) algorithm and the ant colony optimization (ACO). These three EAs are applied to five WDS benchmarking case studies with different scales and complexities, and a set of five metrics are used to measure their run-time searching quality and convergence properties. Results show that the run-time metrics can effectively reveal the underlying searching mechanisms associated with each EA, which significantly goes beyond the knowledge from the traditional end-of-run solution statistics. It is observed that the DE is able to identify better solutions if moderate and large computational budgets are allowed due to its great ability in maintaining the balance between the exploration and exploitation. However, if the computational resources are rather limited or the decision has to be made in a very short time (e.g., real-time WDS operation), the GA can be a good choice as it can always identify better solutions than the DE and ACO at the early searching stages. Based on the results, the ACO performs the worst for the five case study considered. The outcome of this study is the offer of guidance for the algorithm selection based on the available computation resources, as well as knowledge into the EA’s underlying searching behaviours.

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