Comparison of demand driven and pressure dependent hydraulic approaches for modelling water quality in distribution networks

Water distribution hydraulic models have been used as a basis for water quality modelling in distribution networks. Experts recognized that a realistic hydraulic model is required to accurately simulate water quality. The aim of this paper is to compare Demand Driven Analysis (DDA) and Pressure Dependent Analysis (PDA) based hydraulic models for simulating water quality in networks for future enhancement of water quality models. The well known EPANET 2 and the newly developed EPANET-PDX (pressure dependent extension) have been used as the DDA and PDA models respectively. Water quality analysis was performed for normal and pressure deficient hydraulic conditions on a sample network from literature. The models provide identical results for normal pressure conditions, but different results for pressure deficient conditions. The differences for the case of pressure deficient condition are significant at the farthest nodes from the source during high pressure deficiency situation with low demand satisfaction condition

Assessment of water quality modelling capabilities of EPANET multi-species and pressure dependent extension models

The need for accurately predicting water quality through models has increasingly been crucial in meeting rigorous standards and customer expectations. There are several endeavours on developing robust water quality models for water distribution systems. In this paper, two variants of the EPANET 2 water quality model have been assessed to inform future research. The models are the multiple species extension EPANET-MSX and the pressure-dependent extension EPANET-PDX. Water quality analysis was conducted on a hypothetical network considering various operating pressure conditions. Different kinetic models were employed to simulate water quality. First order, limited first order and zero order models were used for predicting chlorine residual, disinfection by-products (DBPs) and water age respectively. Generally, EPANET-MSX and EPANET-PDX provided identical water quality results for normal operating conditions with adequate pressure but different results for pressure-deficient networks. Also, a parallel first order model with fast and slow reacting components was used for chlorine decay and DBPs using the EPANET-MSX model for a network operating under normal pressure conditions

Penalty-free multi-objective evolutionary approach to optimization of anytown water distribution network

This paper describes the development and application of a new multi-objective evolutionary optimization approach for the design and upgrading of water distribution systems with multiple pumps and service reservoirs. The optimization model employs a pressure-driven analysis simulator that accounts for the minimum node pressure constraints and conservation of mass and energy. Pump scheduling, tank siting and tank design are integrated seamlessly in the optimization without introducing additional heuristic procedures. The computational solution of the optimization problem is entirely penalty-free, thanks to pressure-driven analysis and the inclusion of explicit criteria for tank depletion and replenishment. The model was applied to the Anytown network that is a benchmark optimization problem. Many new solutions were achieved that are cheaper and offer superior performance compared to previous solutions in the literature. Detailed and extensive simulations of the solutions achieved were carried out. Spatial and temporal variations in water quality were investigated by simulating the chlorine residual and disinfection by-products in addition to water age. The hydraulic requirements were satisfied; efficiency of pumps was consistently high; effective operation of the new and existing tanks was achieved; water quality was improved; and overall computational efficiency was high. The formulation is entirely generic

Practical application of penalty-free evolutionary multi-objective optimisation of water distribution systems

Evolutionary algorithms are a commonly applied optimisation approach in water distribution systems. However, the algorithms are time consuming when applied to large optimisation problems. The aim of this paper is to evaluate the application of a penalty-free multi-objective evolutionary optimisation algorithm to solve a real-world network design problem. The optimization model uses pressure-dependent analysis that accounts for the pressure dependency of the nodal flows and thus avoids the need for penalties to address violations of the nodal pressure constraints. The algorithm has been tested previously using benchmark optimisation problems in the literature. In all cases, the algorithm found improved solutions and/or the best solution reported previously in the literature with considerably fewer function evaluations. In this paper, a real-world network with over 250 pipes was considered. The network comprises multiple sources, multiple demand categories, many fire flows and involves extended period simulation. Due to the size and complexity of the optimization problem, a high performance computer that comprises multiple cores was used for the computational solution. Multiple optimisation runs were performed concurrently. Overall, the algorithm performs well; it consistently provides least cost solutions that satisfy the system requirements quickly. The least-cost design obtained was over 40% cheaper than the existing network in terms of the pipe costs

Comparison of surrogate measures for the reliability and redundancy of water distribution systems

An investigation into the effectiveness of surrogate measures for the hydraulic reliability and/or redundancy of water distribution systems is presented. The measures considered are statistical flow entropy, resilience index, network resilience and surplus power factor. Looped network designs that are maximally noncommittal to the surrogate reliability measures were considered. In other words, the networks were designed by multi-objective evolutionary optimization free of any influence from the surrogate measures. The designs were then assessed using each surrogate measure and two accurate but computationally intensive measures namely hydraulic reliability and pipe-failure tolerance. The results indicate that by utilising statistical flow entropy, the reliability of the network can be reasonably approximated, with substantial savings in computational effort. The results for the other surrogate measures were often inconsistent. Two networks in the literature were considered. One example involved a range of alternative network topologies. In the other example, based on whole-life cost accounting, alternative design and upgrading schemes for a 20-year design horizon were considered. Pressure-dependent hydraulic modelling was used to simulate pipe failures for the reliability calculations

Optimal Tank Design And Operation Strategy To Enhance Water Quality In Distribution Systems

Water storage tanks are key components of water distribution networks (WDNs) and are primarily designed and operated to meet demand variations and pressure needs. However, the common practice in the design of WDNs is to incorporate large storage tanks that may possibly create long residence time. Long residence time is a major contributing factor for loss of disinfectant, increased formation of disinfection by products and microbial regrowth. Also, poor choice in tank geometry, location and operation can play a role in deterioration of water quality. Most of the previous approaches on optimisation of WDNs design and operation do not take into account tank operation explicitly. In this work, optimal tank design, location and operation strategy has been implemented to assess network performance from water quality perspective. The most recently developed genetic algorithm based optimisation model “Penalty-Free Multi–Objective Evolutionary Algorithm (PF-MOEA)” has been employed. PF-MOEA uses a pressure dependent analysis simulator that handles the node pressure constraints and the conservation of mass and energy inherently. The algorithm considers tank operation strategy as one of the objectives in the optimisation process. The optimisation model incorporates pipe sizing, tank siting, tank sizing and pump operation. PF-MOEA has been applied on the benchmark “Anytown” network that comprises multiple loadings, storage tanks and pumps. The model provided many feasible solutions that are cheaper than the best previous solutions. The solutions satisfy both node pressure and operational constraints for the different loading conditions. A significant improvement in water quality has been achieved in terms of water age, disinfection residual and disinfection by-product concentration in the entire network. Results demonstrated that explicit consideration of the tank operation objective has substantially enhanced the network performance in reference to hydraulic as well as water quality

Pressure-dependent EPANET extension

In water distribution systems (WDSs), the available flow at a demand node is dependent on the pressure at that node. When a network is lacking in pressure, not all consumer demands will be met in full. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable and represents the main limitation of the conventional demand driven analysis (DDA) approach to WDS modelling. A realistic depiction of the network performance can only be attained by considering demands to be pressure dependent. This paper presents an extension of the renowned DDA based hydraulic simulator EPANET 2 to incorporate pressure-dependent demands. This extension is termed “EPANET-PDX” (pressure-dependent extension) herein. The utilization of a continuous nodal pressure-flow function coupled with a line search and backtracking procedure greatly enhance the algorithm’s convergence rate and robustness. Simulations of real life networks consisting of multiple sources, pipes, valves and pumps were successfully executed and results are presented herein. Excellent modelling performance was achieved for analysing both normal and pressure deficient conditions of the WDSs. Detailed computational efficiency results of EPANET-PDX with reference to EPANET 2 are included as well

Penalty-free feasibility boundary convergent multi-objective evolutionary algorithm for the optimization of water distribution systems

This paper presents a new penalty-free multi-objective evolutionary approach (PFMOEA) for the optimization of water distribution systems (WDSs). The proposed approach utilizes pressure dependent analysis (PDA) to develop a multi-objective evolutionary search. PDA is able to simulate both normal and pressure deficient networks and provides the means to accurately and rapidly identify the feasible region of the solution space, effectively locating global or near global optimal solutions along its active constraint boundary. The significant advantage of this method over previous methods is that it eliminates the need for ad-hoc penalty functions, additional “boundary search” parameters, or special constraint handling procedures. Conceptually, the approach is downright straightforward and probably the simplest hitherto. The PFMOEA has been applied to several WDS benchmarks and its performance examined. It is demonstrated that the approach is highly robust and efficient in locating optimal solutions. Superior results in terms of the initial network construction cost and number of hydraulic simulations required were obtained. The improvements are demonstrated through comparisons with previously published solutions from the literature