A Graph-Theoretic Framework for Assessing the Resilience of Sectorised Water Distribution Networks

Self Cite

Cities depend on multiple heterogeneous, interconnected infrastructures to provide safe water to consumers. Given this complexity, efficient numerical techniques are needed to support optimal control and management of a water distribution network (WDN). This paper introduces a holistic analysis framework to support water utilities on the decision making process for an efficient supply management. The proposal is based on graph spectral techniques that take advantage of eigenvalues and eigenvectors properties of matrices that are associated with graphs. Instances of these matrices are the adjacency matrix and the Laplacian, among others. The interest for this application is to work on a graph that specifically represents a WDN. This is a complex network that is made by nodes corresponding to water sources and consumption points and links corresponding to pipes and valves. The aim is to face new challenges on urban water supply, ranging from computing approximations for network performance assessment to setting device positioning for efficient and automatic WDN division into district metered areas. It is consequently created a novel tool-set of graph spectral techniques adapted to improve main water management tasks and to simplify the identification of water losses through the definition of an optimal network partitioning.Two WDNs are used to analyze the proposed methodology. Firstly, the well-known network of C-Town is investigated for benchmarking of the proposed graph spectral framework. This allows for comparing the obtained results with others coming from previously proposed approaches in literature. The second case-study corresponds to an operational network. It shows the usefulness and optimality of the proposal to effectively manage a WDN.

Section: Case Studymentioning

confidence: 99%

Applications of Graph Spectral Techniques to Water Distribution Network Management

Nardo

Giudicianni

Greco

et al. 2018

Self Cite

“…Therefore, a water network including the nodes with low value of water-flow closeness and K-shortest path can be considered as a system with low resilience. Herrera et al [42] extended these resilience measures for large-scale water networks. A water distribution network can be divided into sub-networks using sectorization approaches such as graph clustering, spectral clustering, and multi-level partitioning [78].…”

Section: Overview Of the Selected Resilience Measuresmentioning

confidence: 99%

A Systematic Review of Quantitative Resilience Measures for Water Infrastructure Systems

Shin

Lee

Judi

et al. 2018

151

Abstract:Over the past few decades, the concept of resilience has emerged as an important consideration in the planning and management of water infrastructure systems. Accordingly, various resilience measures have been developed for the quantitative evaluation and decision-making of systems. There are, however, numerous considerations and no clear choice of which measure, if any, provides the most appropriate representation of resilience for a given application. This study provides a critical review of quantitative approaches to measure the resilience of water infrastructure systems, with a focus on water resources and distribution systems. A compilation of 11 criteria evaluating 21 selected resilience measures addressing major features of resilience is developed using the Axiomatic Design process. Existing gaps of resilience measures are identified based on the review criteria. The results show that resilience measures have generally paid less attention to cascading damage to interrelated systems, rapid identification of failure, physical damage of system components, and time variation of resilience. Concluding the paper, improvements to resilience measures are recommended. The findings contribute to our understanding of gaps and provide information to help further improve resilience measures of water infrastructure systems.

“…This helps the decision maker to understand the partitioning schemes and thus make an informed decision. Additionally, quantitative evaluation is usually conducted to examine the effect of the partitioning [12,28,29]. In this paper, several indicators in the context of topological analysis are proposed to quantify the performance of partitioning methods.…”

Section: Evaluation Indicatorsmentioning

confidence: 99%

Comparing Topological Partitioning Methods for District Metered Areas in the Water Distribution Network

Liu

Zhao

Zhang

et al. 2018

This paper presents a comparative analysis of three partitioning methods, including Fast Greedy, Random Walk, and Metis, which are commonly used to establish the district metered areas (DMAs) in water distribution systems. The performance of the partitioning methods is compared using a spectrum of evaluation indicators, including modularity, conductance, density, expansion, cuts, and communication volume, which measure different topological characteristics of the complex network. A complex water distribution network EXNET is used for comparison considering two cases, i.e., unweighted and weighted edges, where the weights are represented by the demands. The results obtained from the case study network show that the Fast Greedy has a good overall performance. Random Walk can obtain the relative small cut edges, but severely sacrifice the balance of the partitions, in particular when the number of partitions is small. The Metis method has good performance on balancing the size of the clusters. The Fast Greedy method is more effective in the weighted graph partitioning. This study provides an insight for the application of the topology-based partitioning methods to establish district metered areas in a water distribution network.Recent research has focused on the development of topology-based partitioning methods (e.g., graph theory, Metis, and Random Walk) to consider more network attributes. Most recently, Perelman et al. [3] developed a network partitioning approach from a practical perspective, in which the distribution network is partitioned based on the backbone transmission pipes identified in the first step. The Metis partitioning method [11] was used to divide the network topology into DMAs. Moreover, the water sources should be regarded as the main control elements for network partitioning [12] so that the source supply areas have the least influence on the hydraulic performance of the isolated zones and the finer communities are further divided by a graph partitioning method. Wright et al. [13] introduced the concept of dynamically-controlled DMAs for burst identification and leakage estimation, and it can be used to improve system resilience to permanent valve closures. The Walktrap algorithm, which is also referred to as Random Walk [14,15], was used to trap the walker in the dense cluster, and partition the water distribution network accordingly [16]. The aforementioned studies are the straightforward applications to network partitioning, however, the mechanism, characteristic, and applicability of the graphical partitioning methods (i.e., Metis, Random Walk) are not properly addressed. Moreover, there is no comprehensive comparison of the various topology partitioning algorithms and, therefore, it is difficult to determine which algorithm is more suitable and, thus, should be used for WDS partitioning in practice.Network partitioning can be assessed using hydraulic indicators and topological indicators. Additionally, economic criteria can also be used to consider the costs and benefits involved by the...