Abstract
Optimization of water distribution networks can effectively reduce their annual cost, which includes the average investment for each year the operational costs and depreciation costs. However, the existing optimization models rarely directly consider the basic flow of each node in case of accidents, such as pipe bursts. Therefore, it is necessary to check the flow requirements under accident conditions. In order to deal with these drawbacks, two optimization models are established considering accident conditions: a single-objective optimization model considering annual cost as an economic objective, and a multi-objective optimization model with a reliability objective defined by the surplus water head. These models are solved based on the genetic algorithm, non-dominated sorting genetic algorithm-II algorithm and Levenberg-Marquardt iterative method. Applying two cases of a single pump station and a multi pump water station water supply, it is shown that the annual cost when considering the accident conditions is higher than that without considering the accident conditions. Moreover, the annual cost obtained with the multi-objective optimization model is slightly higher than that obtained with the single-objective optimization model. The cost is higher because the former model reduces the average surplus water head, which can improve the water distribution network reliability. Therefore, the model and optimization algorithm proposed in this paper can provide a general and fast optimization tool for water distribution network optimization.
Highlights
Water Distribution Networks (WDNs) form a part of the critical municipal infrastructure
The circular was used to mark the results of multiobjective optimization while considering accident conditions on the coordinate axis
The diamond is used to mark the results of multi‐objective optimization without considering diamond is used to mark the results of multi-objective optimization without considering accident conditions on the coordinate axis
Summary
Water Distribution Networks (WDNs) form a part of the critical municipal infrastructure. These are very complex systems that require a high investment in their construction and maintenance [1]. A suitable WDN should be able to provide water with the required pressure. In case of accident conditions such as a pipe burst, a WDN must provide a minimum acceptable flow and pressure at each node. Optimization of WDNs is used to reduce their annual costs, and ensure the reliability of WDN operation by reasonably selecting the pipe diameter of each section under different operating conditions. The main focus of the research on WDN optimization is to minimize their costs [2,3,4,5]
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