Improving the resilience of post-disaster water distribution systems using a dynamic optimization framework

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Improving the resilience of water distribution systems (WDSs) to handle natural disasters (e.g., earthquakes) is a critical step towards sustainable urban water management. This requires the water utility to be able to respond quickly to such disaster events and in an organized manner, to prioritize the use of available resources to restore service rapidly whilst minimizing the negative impacts. Many methods have been developed to evaluate the WDS resilience, but few efforts are made so far to improve resilience of a post-disaster WDS through identifying optimal sequencing of recovery actions. To address this gap, a new dynamic optimization framework is proposed here where the resilience of a post-disaster WDS is evaluated using six different metrics. A tailored Genetic Algorithm is developed to solve the complex optimization problem driven by these metrics. The proposed framework is demonstrated using a real-world WDS with 6,064 pipes. Results obtained show that the proposed framework successfully identifies near-optimal sequencing of recovery actions for this complex WDS. The gained insights, conditional on the specific attributes of the case study, include: (i) the near-optimal sequencing of recovery strategy heavily depends on the damage properties of the WDS, (ii) replacements of damaged elements tend to be scheduled at the intermediate-late stages of the recovery process due to their long operation time, and (iii) interventions to damaged pipe elements near critical facilities (e.g., hospitals) should not be necessarily the first priority to recover due to complex hydraulic interactions within the WDS

Embracing Analytics in the Drinking Water Industry

Analytics can support numerous aspects of water industry planning, management, and operations. Given this wide range of touchpoints and applications, it is becoming increasingly imperative that the championship and capability of broad-based analytics needs to be developed and practically integrated to address the current and transitional challenges facing the drinking water industry. Analytics will contribute substantially to future efforts to provide innovative solutions that make the water industry more sustainable and resilient. The purpose of this book is to introduce analytics to practicing water engineers so they can deploy the covered subjects, approaches, and detailed techniques in their daily operations, management, and decision-making processes. Also, undergraduate students as well as early graduate students who are in the water concentrations will be exposed to established analytical techniques, along with many methods that are currently considered to be new or emerging/maturing. This book covers a broad spectrum of water industry analytics topics in an easy-to-follow manner. The overall background and contexts are motivated by (and directly drawn from) actual water utility projects that the authors have worked on numerous recent years. The authors strongly believe that the water industry should embrace and integrate data-driven fundamentals and methods into their daily operations and decision-making process(es) to replace established ìrule-of-thumbî and weak heuristic approaches ñ and an analytics viewpoint, approach, and culture is key to this industry transformation

Water Distribution System Modeling and Optimization: A Case Study

In the last years, the scientific literature has reported an increasing use of hydraulic models to describe water distribution systems (WDS). Hydraulic models represent tools for managing the complexity of WDSs, and a number of optimization methods have been proposed to improve the performance of these infrastructures. However, because of the lack of available data on WDSs many works have only considered synthetic WDS with idealized behaviour or small-sized WDSs with simple topology and limited complexity. This lack of complex case studies has often hindered the demonstration of the potential of hydraulic models and of the optimization approaches relying on their use. In this work, we present a case study about a real large WDS. The system is composed of approximately 3000 pipes (>170 km) and 3000 demand nodes (corresponding to 50,000 users) that are spread across a hilly area over a 200 m elevation gradient. Water is provided by ten wells and it is distributed by five pumping stations and four tanks at different elevations. Pump operation is partly automatically controlled by water levels in tanks and partly by a fixed temporal schedule. This complexity results in a nontrivial hydraulic behaviour that is well reproduced by our hydraulic model. The model is also used with a multi-objective genetic algorithm solver to identify different operational scenarios that lead to a reduction of energy consumption and water leakages

Enhanced Pump Schedule Optimization For Large Water Distribution Networks To Maximize Environmental And Economic Benefits

For more than four decades researchers tried to develop optimization method and tools to reduce electricity consumption of pump stations of water distribution systems. Based on this ongoing research trend, about a decade ago, some commercial pump operation optimization software introduced to the market. Using metaheuristic and evolutionary techniques (e.g. Genetic Algorithm) make some commercial and research tools able to optimize the electricity cost of small water distribution systems (WDS). Still reducing the environmental footprint of these systems and dealing with large and complicated water distribution system is a challenge. In this study, we aimed to develop a multiobjective optimization tool (PEPSO) for reducing electricity cost and pollution emission (associated with energy consumption) of pump stations of WDSs. PEPSO designed to have a user-friendly graphical interface besides the state of art internal functions and procedures that lets users define and run customized optimization scenarios for even medium and large size WDSs. A customized version of non-dominated sorting genetic algorithm II is used as the core optimizer algorithm. EPANET toolkit is used as the hydraulic solver of PEPSO. In addition to the EPANET toolkit, a module is developed for training and using an artificial neural network instead of the high fidelity hydraulic model to speed up the optimization process. A unique measure that is called “Undesirability” is also introduced and used to help PEPSO in finding the promising path of optimization and making sure that the final results are desirable and practical. PEPSO is tested for optimizing the detailed hydraulic model of WDS of Monroe city, MI, USA and skeletonized hydraulic model of WDS of Richmond, UK. The various features of PEPSO are tested under 8 different scenarios, and its results are compared with results of Darwin Scheduler (a well-known commercial software in this field). The test results showed that in a reasonable amount of time, PEPSO is able to optimize and provide logical results for a medium size WDS model with 13 pumps and thousands of system components under different scenarios. It also is concluded that this tool in many aspects can provide better results in comparison with the famous commercial optimization tool in the market

Optimal Scheduling of Variable Speed Pumps Using Mixed Integer Linear Programming -- Towards An Automated Approach

This article describes the methodology for formulating and solving optimal pump scheduling problems with variable-speed pumps (VSPs) as mixed integer linear programs (MILPs) using piece-linear approximations of the network components. The water distribution network (WDN) is simulated with an initial pump schedule for a defined time horizon, e.g. 24 hours, using a nonlinear algebraic solver. Next, the network element equations including VSPs are approximated with linear and piece-linear functions around chosen operating point(s). Finally, a fully parameterized MILP is formulated in which the objective is the total pumping cost. The method was used to solve a pump scheduling problem on a a simple two variable speed pump single-tank network that allows the reader to easily understand how the methodology works and how it is applied in practice. The obtained results showed that the formulation is robust and the optimizer is able to return global optimal result in a reliable manner for a range of operating points.Comment: Presented at 19th Computing and Control for the Water Industry Conference, CCWI 202

TRANSIENT-BASED RISK ANALYSIS OF WATER DISTRIBUTION SYSTEMS

Water distribution system utilities must be able to maintain a system’s assets (i.e., pumps, tanks, water mains, etc.) in good working condition in order to provide adequate water quantity and quality to its customers. Various asset management approaches are employed by utilities in order to make optimal decisions regarding the renewal of system components. Part of a good asset management approach is performing a comprehensive risk analysis which consists of considering all potential ways in which the system may fail, the likelihood failure of for each scenario, and the consequences of said failure. This study investigates a water distribution system’s risk of failure due to both acute transient events (e.g., pump trip) and standard pressure fluctuations due to daily system operations. Such an analysis may be useful in optimal decision making such as asset monitoring, scheduling of condition assessments or system renewal projects, policy implementation, and investment priorities in order to keep the utility’s total costs at a minimum. It may also be useful as a precautionary measure to help prevent catastrophic failures such as large main blowouts for which the utility would incur substantial costs, both direct and indirect. As part of this thesis, a database of water distribution system models is used to analyze the effects of an acute transient event for different system configurations. The database was created at the University of Kentucky and has been made available to the research community to test newly developed algorithms for various studies including optimal system operations and optimal system design

Battle of Postdisaster Response and Restoration

[EN] The paper presents the results of the Battle of Postdisaster Response and Restoration (BPDRR) presented in a special session at the first International water distribution systems analysis & computing and control in the water industry (WDSA/CCWI) Joint Conference, held in Kingston, Ontario, Canada, in July 2018. The BPDRR problem focused on how to respond and restore water service after the occurrence of five earthquake scenarios that cause structural damage in a water distribution system. Participants were required to propose a prioritization schedule to fix the damages of each scenario while following restrictions on visibility/nonvisibility of damages. Each team/approach was evaluated against six performance criteria: (1) time without supply for hospital/firefighting, (2) rapidity of recovery, (3) resilience loss, (4) average time of no user service, (5) number of users without service for eight consecutive hours, and (6) water loss. Three main types of approaches were identified from the submissions: (1) general-purpose metaheuristic algorithms, (2) greedy algorithms, and (3) ranking-based prioritizations. All three approaches showed potential to solve the challenge efficiently. The results of the participants showed that for this network, the impact of a large-diameter pipe failure on the network is more significant than several smaller pipes failures. The location of isolation valves and the size of hydraulic segments influenced the resilience of the system during emergencies. On average, the interruptions to water supply (hospitals and firefighting) varied considerably among solutions and emergency scenarios, highlighting the importance of private water storage for emergencies. 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Kingston Canada: Open Journal Systems

Optimal pump scheduling for urban drainage under variable flow conditions

The paper is focused on the optimal scheduling of a drainage pumping station, complying with variations in the pump rotational speed and a recurrent pattern for the inflow discharge. The paper is structured in several consecutive steps. In the first step, the experimental set-up is described and results of calibration tests on different pumping machines are presented to obtain equations linking significant variables (discharge, head, power, efficiency). Then, those equations are utilized to build a mixed-integer optimization model able to find the scheduling solution that minimizes required pumping energy. The model is solved with respect to a case study referred to a urban drainage system in Naples (Italy) and optimization results are analysed to provide insights on the algorithm computational performance and on the influence of pumping machine characteristics on the overall efficiency savings. With reference to the simulated scenarios, an average value of 32% energy can be saved with an optimized control. Its actual value depends on the hydraulic characteristics of the system

Pump scheduling in drinking water distribution networks with an LP/NLP-based branch and bound

This paper offers a novel approach for computing globally optimal solutions to the pump scheduling problem in drinking water distribution networks. A tight integer linear relaxation of the original non-convex formulation is devised and solved by branch and bound where integer nodes are investigated through non-linear programming to check the satisfaction of the non-convex constraints and compute the actual cost. This generic method can tackle a large variety of networks , e.g. with variable-speed pumps. We also propose to specialize it for a common subclass of networks with several improving techniques, including a new primal heuristic to repair near-feasible integer relaxed solutions. Our approach is numerically assessed on various case studies of the literature and compared with recently reported results

Lost in optimisation of water distribution systems? A literature review of system design

This is the final version of the article. Available from MDPI via the DOI in this record.Optimisation of water distribution system design is a well-established research field, which has been extremely productive since the end of the 1980s. Its primary focus is to minimise the cost of a proposed pipe network infrastructure. This paper reviews in a systematic manner articles published over the past three decades, which are relevant to the design of new water distribution systems, and the strengthening, expansion and rehabilitation of existing water distribution systems, inclusive of design timing, parameter uncertainty, water quality, and operational considerations. It identifies trends and limits in the field, and provides future research directions. Exclusively, this review paper also contains comprehensive information from over one hundred and twenty publications in a tabular form, including optimisation model formulations, solution methodologies used, and other important details