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

Abstract

Optimal rehabilitation of large water distribution systems (WDSs) with many decision variables is often time consuming and computationally expensive. This paper presents a new optimal rehabilitation methodology for WDSs based on the graph theory clustering concept. The methodology starts with partitioning the WDS based on its connectivity properties into a number of clusters (small subsystems). Pipes that might have direct impact on system performance are identified and considered for the rehabilitation problem. Three optimization-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, and (3) a combination of Strategies 1 and 2. In all optimization strategies, the decision variables for the rehabilitation problem are the diameters of duplicated pipes; the objective functions are to minimize the total cost of duplicated pipes and 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 was also compared to the full search space optimization strategy and engineering judgment–based optimization strategy in which all pipes and selection of pipes are considered as decision variables, respectively. The results show that Strategy 3 is able to generate solutions with similar performance that are cheaper by around 53% and 35% in comparison with the full search space and engineering judgment–based optimization strategies, respectively. The results also demonstrate that the cluster-based approach can reduce the computational efforts for achieving optimum solutions compared to the other optimization strategies.