Optimal Rehabilitation of Water Distribution Systems Using a Cluster-Based Technique

Abstract

Abstract:Optimal rehabilitation of large water distribution system (WDS) with many decision variables is often time-consuming and computationally expensive. This paper presents a new optimal rehabilitation methodology for WDSs based on graph theory clustering concept. The methodology starts with partitioning the WDS based on its connectivity properties into a number of clusters (small sub-systems). Pipes which might have direct impact on system performance are identified and considered for rehabilitation problem. Three optimisation-based strategies are then considered for pipe rehabilitation in the clustered network: 1) rehabilitation of some of the pipes inside the clusters; 2) rehabilitation of pipes in the path supplying water to the clusters; 3) combination of strategies 1 and 2. In all optimisation strategies, the decision variables are the diameters of duplicated pipes; the objective functions are to minimise the total cost of duplicated pipes and to minimise the number of nodes with pressure deficiency. The performance of proposed strategies was demonstrated in a large WDS with pressure deficiencies. The performance of these strategies were also compared to the full search space optimisation strategy and engineering judgement based optimisation strategy in which all pipes or selection of pipes are considered as decision variables respectively. The results show that strategy 3 is able to provide the best Pareto optimal front. The results also demonstrate that the cluster-based approach can significantly reduce the computational efforts for achieving optimum rehabilitation compared to the other optimization strategies. Optimal rehabilitation of large water distribution system (WDS) with many decision variables, 25 is often time-consuming and computationally expensive. This paper presents a new optimal 26 rehabilitation methodology for WDSs based on graph theory clustering concept. The methodology 27 starts with partitioning the WDS based on its connectivity properties into a number of clusters (small 28 sub-systems). Pipes which might have direct impact on system performance are identified and 29 considered for rehabilitation problem. Three optimisation-based strategies are then considered for 30 pipe rehabilitation in the clustered network: 1) rehabilitation of some of the pipes inside the clusters; 31 Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation2) rehabilitation of pipes in the path supplying water to the clusters; 3) combination of strategies 1 32 and 2. In all optimisation strategies, the decision variables are the diameters of duplicated pipes; the 33 objective functions are to minimise the total cost of duplicated pipes and to minimise the number of 34 nodes with pressure deficiency. 35The performance of proposed strategies was demonstrated in a large WDS with pressure 36 deficiencies. The performance of these strategies were also compared to the full search space 37 optimisation strategy and engineering judgement based optimisation strategy in which all pipes or...

Lost in Optimisation of Water Distribution Systems? A Literature Review of System Design

“…Lastly, methodological improvements using existing methods have been proposed rather than applying/developing new algorithms, with the aim to improve computational efficiency. Those improvements represent multiple-phase optimisation concepts [30], which can be combined with graph decomposition [46,69] or clustering [90] techniques.…”

“…Pressure deficit at customer demand nodes (maximum individual or total), or the number of demand nodes with the pressure deficit [65] (maximum individual deficit), [66,68] (total deficit), [90] (the number of demand nodes)…”

Optimal Operation of Water Distribution Systems Using a Graph Theory–Based Configuration of District Metered Areas

“…The method is implemented by using an open source and free software called "Gephi" which is widely used for graph network visualisation and manipulation (Gephi, 2014). The WDS clustering is carried out in two steps (Muhammed et al 2017): 1) the WDS is mapped into an undirected graph in which the vertices represent nodes, reservoirs and tanks and the edges represent pipes, pumps and valves; 2) the graph is divided into clusters of vertices characterised by stronger interconnections based on the modularity index, a metric to be maximised during clustering, which is defined as:…”

“…Division of WDS into smaller zones, so-called District Metered Areas (DMAs), is a common approach particularly in the UK for a better management of water demands in WDS (Walski et al 2003). Other applications of the DMA are to reduce water loss and pressure management (Thornton et al 2008, Laucelli et al 2017, protect network water quality (Di Nardo et al 2013, Zhang et al 2017 and improve optimal rehabilitation of WDS (Muhammed et al 2017). Each DMA is isolated by valves and connected to the rest of WDS by a small number of inlet and outlet water mains.…”

Métodos de partição de rede de abastecimento de água: um estudo de caso em Pederneiras/SP

“…OATES, 2000;KITA et al, 1996;CORNE, 2000;OSYCZKA;KUNDU, 1996). HAJEBI et al, 2014;MAKAREMI;HAGHIGHI;GHAFOURI, 2017;MUHAMMED et al, 2017).…”