Comparison Of Various Phased Approaches For The Constrained Minimum-Cost Design Of Water Distribution Networks

This work is aimed at analyzing and comparing three different phased approaches for constrained minimum-cost design of water distribution networks: the single-step design with demand feedback, the multi-step design without demand feedback and the multi-step design with demand feedback. The difference between the single-step design and the multi-step design lies in the fact that whereas the former entails optimizing a single construction step at a time, i.e. the current construction phase, the latter is based on the phasing of construction and then is aimed at optimizing the current construction phase and all the subsequent phases, included inside a certain temporal horizon, simultaneously. The demand feedback is here used as a pragmatic tool for updating the forecast at some specific time instant of the future demand growth: such an update is performed by setting the future demand growth equal to that really observed in the previous time step. Alternatively, the predicted demand growth rate at the generic time instant can be kept equal to the value assumed at the time instant when the generic node appears, without taking account of the demand variation really observed in time in the node (absence of demand feedback). Applications to a real case study show that the multi-step design with the demand feedback is the most reliable because it makes it possible to reduce the overall construction costs while attenuating the occurrence of pressure deficits in the various construction steps of the network

Minimum transport-driven algorithm for water distribution network partitioning

Abstract This paper presents a novel algorithm driven by the minimization of the transport function for the partitioning of water distribution networks (WDNs) into district metered areas (DMAs). The algorithm is based on the linear programming (LP) embedded inside a multi-objective genetic algorithm, which enables engineering criteria, such as the minimization of the boundary pipes and the maximization of the uniformity of DMAs, to be considered in the partitioning. Furthermore, the application of the algorithm on the dual network topology based on segments and valves guarantees that configurations of DMAs that respect the real positions of isolation valves for WDN partitioning are obtained. After being described on a small WDN, it is successfully validated on a large size WDN, proving better performance than other algorithms in the scientific literature for the generation of engineeringly appealing DMA configurations, with almost identical hydraulic performance to the unpartitioned WDN

Energy Recovery Optimization by Means of a Turbine in a Pressure Regulation Node of a Real Water Network Through a Data-Driven Digital Twin

In recent years, various devices have been proposed for pressure regulation and energy recovery in water distribution and transport networks. To provide a real net benefit, they require a dedicated long-distance management system in order to carry on both hydrau- lic regulation and electricity production without direct human manual operations. This work presents a new proposal for the management of a pressure regulation system based on the PRS turbine. The proposal is applied to a real water distribution network, named Montescuro Ovest pipeline, at the San Giovannello station. The Real Time Control (RTC) logic currently applied at San Giovannello station is first presented and discussed. A new Advanced Real Time Control (ARTC) logic is then proposed, based on direct configura - tion of the turbine and the surrounding valves as computed by the solution of an optimiza- tion problem. In ARTC a digital twin, including the hydraulic model of the surrounding network, provides a one-to-one relationship between the configuration parameters and the state variables, i.e. flow rates and pressures. The digital twin model equations are continu - ously updated on the basis of the recorded measures. Besides providing almost identical performance to the current RTC logic in the current operational scenario, the improved ARTC is more robust, in that it guarantees better hydropower generation in modified oper- ational scenarios, as shown in specific tests. The proposed methodology constitutes a new approach to regulating the valves in hydroelectric plants which are currently regulated with traditional automation algorithms

Indirect Impact Assessment of Pluvial Flooding in Urban Areas Using a Graph-Based Approach: The Mexico City Case Study

This paper presents the application of a graph-based methodology for the assessment of flood impacts in an urban context. In this methodology, exposed elements are organized as nodes on a graph, which is used to propagate impacts from directly affected nodes to other nodes across graph links. Compared to traditional approaches, the main advantage of the adopted methodology lies in the possibility of identifying and understanding indirect impacts and cascading effects. The application case concerns floods numerically reconstructed in Mexico City in response to rainfall events of increasing return periods. The hazard reconstruction was carried out by using a simplified hydrological/hydraulic model of the urban drainage system, implemented in EPASWMM, the Storm Water Management Model developed by the United States Environmental Protection Agency. The paper shows how the impacts are propagated along different orders of the impact chain for each return period and compares the risk curves between direct and indirect impact. It also highlights the extent to which the reduction in demand of services from consumers and the loss of services from suppliers are respectively contributing to the final indirect impacts. Finally, it illustrates how different impact mitigation measures can be formulated based on systemic information provided by the analysis of graph properties and taking into account indirect impacts

Comparing Low and High-Level Hybrid Algorithms on the Two-Objective Optimal Design of Water Distribution Systems

The final publication is available at Springer via http://dx.doi.org/10.1007/s11269-014-0823-8This paper presents the comparison of two hybrid methodologies for the two-objective (cost and resilience) design of water distribution systems. The first method is a low-level hybrid algorithm (LLHA), in which a main controller (the non-dominated sorting genetic algorithm II, NSGA-II) coordinates various subordinate algorithms. The second method is a high-level hybrid algorithm (HLHA), in which various sub-algorithms collaborate in parallel. Applications to four case studies of increasing complexity enable the performances of the hybrid algorithms to be compared with each other and with the performance of the NSGA-II. In the case study featuring low/intermediate complexity, the hybrid algorithms (especially the HLHA) successfully capture a more diversified Pareto front, although the NSGA-II shows the best convergence. When network complexity increases, instead, the hybrid algorithms (especially the LLHA) turn out to be superior in terms of both convergence and diversity. With respect to both the HLHA and the NSGA-II, the LLHA is capable of detecting the final front in a single run with a lower computation burden. In contrast, the HLHA and the NSGA-II, which are more affected by the initial random seed, require numerous runs with an attempt to reach the definitive Pareto front. On the other hand, a drawback of the LLHA lies in its reduced ability to deal with general problem formulations, i.e., those not relating to water distribution optimal design.University of ExeterChina Scholarship CouncilEmilia-Romagna Regional Council (Italy

Impact of Hydraulic Variable Conditions in the Solution of Pumping Station Design through Sensitivity Analysis

[EN] A proper pumping station (PS) design should consider multiple criteria, such as technical, economic, and environmental aspects. The analytic hierarchy process (AHP) method can be applied for multi-criteria analysis in this type of engineering design, and it is based on the judgment of a group of experts for the criteria considered. On the other hand, the most common method for PS design is one based solely on economic aspects or life cycle cost (LCC). This paper presents a sensitivity analysis of the impact of the hydraulic conditions of a water distribution network (WDN) on the ultimate solution in two PS design approaches. The first approach was the classic method based on LCC minimization and the second approach was based on multi-criteria analysis by means of AHP accounting for technical, economic, and environmental aspects. In this way, the effects of different meaningful variables for PS design, such as the mean demand, parameters of the setpoint curve, electric tariffs, and interest rates, were evaluated to determine the robustness of the PS solutions obtained. The obtained results of the sensitivity analysis in the case study demonstrated that the PS design based on multiple criteria decision analysis was more reliable and robust than the classic PS design against variations that can occur in a WDN, especially in the mean flow, setpoint curve, and electric tariff. The variations in these parameters of the WDN did not impact the ultimate solutions of the PS design approaches when within the tolerance ranges, but these ranges were wider in the second approach to PS design than in the first approach.Briceño-León, CX.; Iglesias Rey, PL.; Martínez-Solano, FJ.; Creaco, E. (2023). Impact of Hydraulic Variable Conditions in the Solution of Pumping Station Design through Sensitivity Analysis. Water. 15(17):1-23. https://doi.org/10.3390/w15173067123151

Correlation or not correlation? This is the question in modeling residential water demand pulses

Published© 2013 The Authors. Published by Elsevier Ltd. This paper presents a comparison of two different modelling approaches for the generation of residential water demand pulses as Poisson processes. Both approaches are able to preserve the mean value of daily water demand. The main difference lies in the fact that the first considers the correlation between pulse durations and intensities whereas the second neglects it. Overall, the results of the applications aimed at reproducing the measured pulses in two households show that the increase in parameterization burden associated with taking correlation into account delivers a considerable improvement in the quality of model predictions

Forecasting domestic water consumption from smart meter readings using statistical methods and artificial neural networks

PublishedThis paper presents an artificial neural network-based model of domestic water consumption. The model is based on real-world data collected from smart meters, and represents a step toward being able to model real-time smart meter data. A range of input schemas are examined, including real meter readings and summary statistics derived from readings, and it is found that the models can predict some consumption but struggle to accurately match in cases of peak usage

Preserving duration-intensity correlation on synthetically generated water demand pulses

This paper proposes the application of three different methods for preserving the correlation between duration and intensity of synthetically generated water demand pulses. The first two methods, i.e., the Iman and Canover (1982) method and the Gaussian copula (Nelsen, 1999) respectively, are derived from the known statistical approaches, though they had never bee applied to the context of demand pulse generation. The third is a novel methodology developed in this work and is a variation in the Gaussian cupola approach. Applications carried out to reproduce the demand pulses measured in one household prove that the three methods are effective and applicable under general conditions