scholarly journals Water distribution network optimization using maximum entropy under multiple loading patterns

2013 ◽  
Vol 13 (5) ◽  
pp. 1265-1271 ◽  
Author(s):  
Anna M. Czajkowska ◽  
Tiku T. Tanyimboh

This paper proposes a maximum entropy-based multi-objective genetic algorithm approach for the design optimization of water distribution networks (WDNs). The novelty is that in contrast to previous research involving statistical entropy the algorithm can handle multiple operating conditions. We used NSGA II and EPANET 2 and wrote a subroutine that calculates the entropy value for any given WDN configuration. The proposed algorithm is demonstrated by designing a six-loop network that is well known from previous entropy studies. We used statistical entropy to include reliability in the design optimization procedure in a computationally efficient way.

2015 ◽  
Vol 16 (3) ◽  
pp. 599-610 ◽  
Author(s):  
Ho Min Lee ◽  
Do Guen Yoo ◽  
Doosun Kang ◽  
Hwandon Jun ◽  
Joong Hoon Kim

The hydraulic analysis of water distribution networks (WDNs) is divided into two approaches: namely, a demand-driven analysis (DDA) and a pressure-driven analysis (PDA). In the DDA, the basic assumption is that the nodal demand is fully supplied irrespective of the nodal pressure, which is mainly suitable for normal operating conditions. However, in abnormal conditions, such as pipe failures or unexpected increase in demand, the DDA approach may cause unrealistic results, such as negative pressure. To address the shortcomings of DDA, PDA has been considered in a number of studies. For PDA, however, the head-outflow relation (HOR) should be given, which is known to contain a high degree of uncertainty. Here, the DDA-based simulator, EPANET2 was modified to develop a PDA model simulating pressure deficient conditions and a Monte Carlo simulation (MCS) was performed to consider the quantitative uncertainty in HOR. The developed PDA model was applied to two networks (a well-known benchmark system and a real-life WDN) and the results showed that the proposed model is superior to other reported models when dealing with negative pressure under abnormal conditions. In addition, the MCS-based sensitivity analysis presents the ranges of pressure and available discharge, quantifying service reliability of water networks.


2020 ◽  
Vol 18 (5) ◽  
pp. 704-721
Author(s):  
Hamideh Jafari ◽  
Taher Rajaee ◽  
Sara Nazif

Abstract One of the ways to reduce the risk of contaminated water consumption is to optimally locate the quality sensors. These sensors warn users in the case of contamination detection. Analyzing the actual conditions of the contamination which enters the network is faced with many uncertainties. These uncertainties include the dose of contamination, time and location of its entry which have received less attention. Also, the uncertainty in the nodes' water demand causes changes in the distribution and contamination diffusion within the network. The main impetus of the present study is to determine the optimal quality sensor locations in the water distribution network in order to reduce the damage caused by contaminated water consumption prior to the contamination event detection. For this purpose, a parameter is defined as the maximum possible damage for calculating which the vulnerability and importance of the nodes have been considered in addition to the uncertainties in the location and time of the contamination entry. The importance of each node differs from that of other ones. Ranking the importance of the nodes is influenced by both land use and covered population ratio. In this study, six scenarios are defined for the contamination event in the water distribution network. These scenarios consider the effects of varying pollutant dose and the contamination input from nodes which are prone to its entry. Also, the NSGA-II has been utilized in order to minimize the damage with minimum number of sensors. The proposed model is evaluated on a real network in Iran. The results indicate that adding only one or two contamination warning sensors to the proposed locations can lead to the decreasing damage caused by the contaminated water consumption from 54 to 82%. According to the proposed method, the best answer for scenarios 1–6 was obtained for 7, 6, 6, 2, 2 and 2 sensors, respectively. The results showed that the slope of the pollution rate diagram does not change much from 6 sensors upwards in the first three scenarios, and from 4 sensors upwards in the second three scenarios. In scenarios 1–3, with 7, 6 and 6 sensors, respectively, in different nodes, the best placement is for 203–224 equivalent attack population, and in scenarios 4–6, with sensors in nodes 4 and 43, the best placement is for 225–279 equivalent attack population.


2020 ◽  
pp. 1-24
Author(s):  
William B. Yates ◽  
Edward C. Keedwell

A sequence-based selection hyper-heuristic with online learning is used to optimise 12 water distribution networks of varying sizes. The hyper-heuristic results are compared with those produced by five multiobjective evolutionary algorithms. The comparison demonstrates that the hyper-heuristic is a computationally efficient alternative to a multiobjective evolutionary algorithm. An offline learning algorithm is used to enhance the optimisation performance of the hyper-heuristic. The optimisation results of the offline trained hyper-heuristic are analysed statistically, and a new offline learning methodology is proposed. The new methodology is evaluated, and shown to produce an improvement in performance on each of the 12 networks. Finally, it is demonstrated that offline learning can be usefully transferred from small, computationally inexpensive problems, to larger computationally expensive ones, and that the improvement in optimisation performance is statistically significant, with 99% confidence.


Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3404
Author(s):  
Flavia Fuso ◽  
Maria C. Cunha ◽  
Gianfranco Becciu

The traditional approach for the optimization of water distribution networks (WDNs) does not always lead to consistent solutions from an operational point of view. The latest optimization algorithms identify solutions that are “the best solutions” in mathematical terms but that can be less than robust against changes in operating conditions, resulting in the worst case in hydraulically infeasible configurations. Thus, this paper aims to provide a methodology that can synthesize the network performance capabilities under the change in operating conditions with two convergent strategies. The first consists of the implementation of new performance indices (PIs), the demand deficit and the pressure range, and the evaluation of their ability to criticality highlight in operating conditions. The second is the introduction of a new approach to weight the infeasible solutions in the final result, which are those inconsistent with the real hydraulic network performances. The analysis shows that the use of these new indices makes it easier to understand the behavior of the network and to identify any weaknesses. This is true if these indices consider the hydraulically inconsistent solutions that may arise from the simulations of different operation conditions; otherwise, results that poorly represent the real behavior of the network would be obtained.


2012 ◽  
Vol 15 (3) ◽  
pp. 700-716 ◽  
Author(s):  
Kent McClymont ◽  
Ed Keedwell ◽  
Dragan Savić ◽  
Mark Randall-Smith

The optimisation of water distribution networks (WDNs) by evolutionary algorithms has gained much coverage in the literature since it was first proposed in the early 1990s. Despite being well studied, the problem and objectives continue to evolve as demands on water companies change. Motivated by the increased focus on reducing the risk of discolouration, this study examines a three objective version of the WDN design problem which takes into account cost, head excess and discolouration risk. Using this formulation, this paper presents a method for producing optimised network designs aimed at reducing discolouration risk in the network design phase and thus reducing the associated long-term maintenance and operational burdens of the system. This paper discusses the use of a discolouration risk model and, using this model, the optimisation of network design, specifically pipe diameters, to produce a range of high quality self-cleaning networks. The network designs are optimised using the Markov-chain hyper-heuristic (MCHH), a new multi-objective online selective hyper-heuristic. The MCHH is incorporated in to the known NSGA-II and SPEA2 and supplied with a range of heuristics tailored for use on the WDN design problem. The results demonstrate an improvement in performance obtained over the original algorithms.


2020 ◽  
Vol 2 (1) ◽  
pp. 57
Author(s):  
Maria Cristina Morani ◽  
Armando Carravetta ◽  
Claudia D’Ambrosio ◽  
Oreste Fecarotta

Water distribution networks are low-energy efficiency systems, due to the high energy consumption, as well as the large amount of water leakage, which are caused by high pressures in the networks. In this study, the optimal location of pumps as turbines (PATs) within a water distribution network is investigated in order to maximize the production of energy and water savings, as well as minimize installation costs. A literature mathematical model has been employed as reference model and the weaknesses of this previous study have been overcome by new constraints. The main preliminary results of the new optimization procedure will be presented and compared with the literature results. According to the results, the new optimization ensures a good solution, in term of water and energy savings, with low investment cost and a fast return in investment.


2005 ◽  
Vol 5 (2) ◽  
pp. 31-38
Author(s):  
A. Asakura ◽  
A. Koizumi ◽  
O. Odanagi ◽  
H. Watanabe ◽  
T. Inakazu

In Japan most of the water distribution networks were constructed during the 1960s to 1970s. Since these pipelines were used for a long period, pipeline rehabilitation is necessary to maintain water supply. Although investment for pipeline rehabilitation has to be planned in terms of cost-effectiveness, no standard method has been established because pipelines were replaced on emergency and ad hoc basis in the past. In this paper, a method to determine the maintenance of the water supply on an optimal basis with a fixed budget for a water distribution network is proposed. Firstly, a method to quantify the benefits of pipeline rehabilitation is examined. Secondly, two models using Integer Programming and Monte Carlo simulation to maximize the benefits of pipeline rehabilitation with limited budget were considered, and they are applied to a model case and a case study. Based on these studies, it is concluded that the Monte Carlo simulation model to calculate the appropriate investment for the pipeline rehabilitation planning is both convenient and practical.


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.


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