M.E. Castro Gama
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13 records found
1
Journal article
(2024)
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Melina Denardi, Jezabel D. Bianchotti, Mario Castro-Gama, Gabriel D. Puccini
In recent decades, the global imperative to address drinking water scarcity encourages initiatives that ensure a sustainable supply. In this context, this work presents a two-stage methodology designed to reduce background leakages in water distribution networks by controlling pressures during hours of lower water demand using pressure-reducing valves (PRVs). The first stage focuses on dividing the network into smaller structures, or modules, optimizing the topological modularity index. Here, conceptual cuts are determined at the boundaries between modules, identifying them as potential positions for the installation of PRVs. The second stage determines the quantity, optimal settings, and operational status of these valves. Focused on reducing elevated nighttime pressures, the strategy minimizes the network’s nighttime resilience index using simulated annealing for optimization. The application of this methodology to two reference networks results in different levels of PRV activity, achieving a substantial decrease in pressure and nighttime background leakage volumes, without a negative impact on peak demand hours.
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In recent decades, the global imperative to address drinking water scarcity encourages initiatives that ensure a sustainable supply. In this context, this work presents a two-stage methodology designed to reduce background leakages in water distribution networks by controlling pressures during hours of lower water demand using pressure-reducing valves (PRVs). The first stage focuses on dividing the network into smaller structures, or modules, optimizing the topological modularity index. Here, conceptual cuts are determined at the boundaries between modules, identifying them as potential positions for the installation of PRVs. The second stage determines the quantity, optimal settings, and operational status of these valves. Focused on reducing elevated nighttime pressures, the strategy minimizes the network’s nighttime resilience index using simulated annealing for optimization. The application of this methodology to two reference networks results in different levels of PRV activity, achieving a substantial decrease in pressure and nighttime background leakage volumes, without a negative impact on peak demand hours.
Many utilities around the world are required to constantly improve their operations. This is a job which is never fulfilled. Every day demand changes, new elements appear in a system, old elements are replaced and even new sensor technologies are implemented in the field. To better manage these dynamic changes utilities have been shifting towards a digitalization of their daily operations. Within this landscape many different issues which are faced by a utility can be addressed with the help of decision support systems. Such systems may be of particular relevance for issues pertinent to diverse stakeholders such as: operators, customers, decision makers, government and environmental agencies. Among the issues which are more relevant to operators are the continuous supply of water demands, and at an acceptable water quality level. As long as this is achieved, most utilities satisfy their customers. However, this does not come without costs. Reduction of operational costs is always in the loop of discussion of every utility, associated with operational actions such as reducing leakages, reducing energy consumption, reducing pipe breaks and overall improvement of asset management.
This research deals with two different aspects of operations of water distribution networks related to energy minimization and pressure management. Both problems are dealt through model-based optimization via pump scheduling and water network sectorization. The research findings are a stepping stone to improved operation of large water distribution systems where assets are known and there is a need for improvement of energy use. Both optimization problems have been performed using simulations made with EPANET 2.0, linked to heuristic algorithms. Due to the large number of optimization runs, High Performance Computing (HPC) was also employed, using the national computing grid of the Netherlands for research and educational institutions, named SURFSara HPC Cloud, and, to some extent using Microsoft Azure®..... ...
This research deals with two different aspects of operations of water distribution networks related to energy minimization and pressure management. Both problems are dealt through model-based optimization via pump scheduling and water network sectorization. The research findings are a stepping stone to improved operation of large water distribution systems where assets are known and there is a need for improvement of energy use. Both optimization problems have been performed using simulations made with EPANET 2.0, linked to heuristic algorithms. Due to the large number of optimization runs, High Performance Computing (HPC) was also employed, using the national computing grid of the Netherlands for research and educational institutions, named SURFSara HPC Cloud, and, to some extent using Microsoft Azure®..... ...
Many utilities around the world are required to constantly improve their operations. This is a job which is never fulfilled. Every day demand changes, new elements appear in a system, old elements are replaced and even new sensor technologies are implemented in the field. To better manage these dynamic changes utilities have been shifting towards a digitalization of their daily operations. Within this landscape many different issues which are faced by a utility can be addressed with the help of decision support systems. Such systems may be of particular relevance for issues pertinent to diverse stakeholders such as: operators, customers, decision makers, government and environmental agencies. Among the issues which are more relevant to operators are the continuous supply of water demands, and at an acceptable water quality level. As long as this is achieved, most utilities satisfy their customers. However, this does not come without costs. Reduction of operational costs is always in the loop of discussion of every utility, associated with operational actions such as reducing leakages, reducing energy consumption, reducing pipe breaks and overall improvement of asset management.
This research deals with two different aspects of operations of water distribution networks related to energy minimization and pressure management. Both problems are dealt through model-based optimization via pump scheduling and water network sectorization. The research findings are a stepping stone to improved operation of large water distribution systems where assets are known and there is a need for improvement of energy use. Both optimization problems have been performed using simulations made with EPANET 2.0, linked to heuristic algorithms. Due to the large number of optimization runs, High Performance Computing (HPC) was also employed, using the national computing grid of the Netherlands for research and educational institutions, named SURFSara HPC Cloud, and, to some extent using Microsoft Azure®.....
This research deals with two different aspects of operations of water distribution networks related to energy minimization and pressure management. Both problems are dealt through model-based optimization via pump scheduling and water network sectorization. The research findings are a stepping stone to improved operation of large water distribution systems where assets are known and there is a need for improvement of energy use. Both optimization problems have been performed using simulations made with EPANET 2.0, linked to heuristic algorithms. Due to the large number of optimization runs, High Performance Computing (HPC) was also employed, using the national computing grid of the Netherlands for research and educational institutions, named SURFSara HPC Cloud, and, to some extent using Microsoft Azure®.....
Water distribution network (WDN) models are a common decision support tool for understanding the behavior and performance of WDNs, aiding in the planning and management of WDN systems. The increasing availability of real-time data has recently promoted the exploration of Data Assimilation (DA) techniques to improve these models. However, flow, pressure and demand data are uncertain, particularly due to sensor characteristics such as precision and noise. An open question is to what extent DA can still improve hydraulic models when the data used to this end is uncertain. This paper proposes a three-step Ensemble Kalman Filter based DA approach for WDNs (3-EnKF-WDN), building on previous approaches, and advancing in two main fronts: the use of extended period simulation, and the use of pressure-dependent demand (PDD) analysis. Different scenarios considering uncertain sensor data, with varied precision and noise, are applied to two networks of different sizes, representative of real-world WDNs. The computational demand of the 3-EnKF-WDN method is also assessed. Results show that increasing sensor’s precision and decreasing the noise in state measurements reduce model error, as expected. However, we also found that model errors: 1) are reduced more effectively by using 3-EnKF-WDN than by increasing sensors’ precision; 2) are not reduced if certain noise thresholds are surpassed; 3) can be reduced without assimilating demand data if the WDNs are fully monitored with head sensors in all the nodes and flow sensors in all the links.
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Water distribution network (WDN) models are a common decision support tool for understanding the behavior and performance of WDNs, aiding in the planning and management of WDN systems. The increasing availability of real-time data has recently promoted the exploration of Data Assimilation (DA) techniques to improve these models. However, flow, pressure and demand data are uncertain, particularly due to sensor characteristics such as precision and noise. An open question is to what extent DA can still improve hydraulic models when the data used to this end is uncertain. This paper proposes a three-step Ensemble Kalman Filter based DA approach for WDNs (3-EnKF-WDN), building on previous approaches, and advancing in two main fronts: the use of extended period simulation, and the use of pressure-dependent demand (PDD) analysis. Different scenarios considering uncertain sensor data, with varied precision and noise, are applied to two networks of different sizes, representative of real-world WDNs. The computational demand of the 3-EnKF-WDN method is also assessed. Results show that increasing sensor’s precision and decreasing the noise in state measurements reduce model error, as expected. However, we also found that model errors: 1) are reduced more effectively by using 3-EnKF-WDN than by increasing sensors’ precision; 2) are not reduced if certain noise thresholds are surpassed; 3) can be reduced without assimilating demand data if the WDNs are fully monitored with head sensors in all the nodes and flow sensors in all the links.
Journal article
(2021)
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Pilar Conejos, Mario Castro-Gama, Fernando Martinez-Alzamora, Ina Vertommen
A digital twin (DT) is a virtual copy (a digital model) of a real system continuously fed with data to mimic the systems’ past, present and future behaviour. This makes it possible to detect anomalies, test new ideas and changes in the virtual system and assess how it reacts, minimizing the risks to the real system. In this sense, the DT can be seen as a playground to explore the effects of different scenarios and to practice how to best react and operate the physical system under these circumstances. The concept of DT has been used traditionally in the industry field1 but it can also be developed and exploited in a city management context, and in particular in Water Supply and Distribution Networks (WSDN), where it can be applied to all aspects of the system
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A digital twin (DT) is a virtual copy (a digital model) of a real system continuously fed with data to mimic the systems’ past, present and future behaviour. This makes it possible to detect anomalies, test new ideas and changes in the virtual system and assess how it reacts, minimizing the risks to the real system. In this sense, the DT can be seen as a playground to explore the effects of different scenarios and to practice how to best react and operate the physical system under these circumstances. The concept of DT has been used traditionally in the industry field1 but it can also be developed and exploited in a city management context, and in particular in Water Supply and Distribution Networks (WSDN), where it can be applied to all aspects of the system
Journal article
(2021)
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Jezabel D. Bianchotti, Melina Denardi, Mario Castro-Gama, Gabriel D. Puccini
Sectorization is an effective technique for reducing the complexities of analyzing and managing of water systems. The resulting sectors, called district metering areas (DMAs), are expected to meet some requirements and performance criteria such as minimum number of intervention, pressure uniformity, similarity of demands, water quality and number of districts. An efficient methodology to achieve all these requirements together and the proper choice of a criteria governing the sectorization is one of the open questions about optimal DMAs design. This question is addressed in this research by highlighting the advantages of three different criteria when applied to real-word water distribution networks (WDNs). To this, here it is presented a two-stage approach for optimal design of DMAs. The first stage, the clustering of the system, is based on a Louvain-type greedy algorithm for the generalized modularity maximization. The second stage, the physical dividing of the system, is stated as a two-objective optimization problem that utilises the SMOSA version of simulated annealing for multiobjective problems. One objective is the number of isolation valves whereas for the second objective three different performance indices (PIs) are analyzed and compared: (a) standard deviation, (b) Gini coefficient and (c) loss of resilience. The methodology is applied to two real case studies where the first two PIs are optimized to address similar demands among DMAs. The results demonstrate that the proposed method is effective for sectorization into independent DMAs with similar demands. Surprisingly, it found that for the real studied systems, loss of resilience achieves better performance for each district in terms of pressure uniformity and demand similarity than the other two specific performance criteria.
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Sectorization is an effective technique for reducing the complexities of analyzing and managing of water systems. The resulting sectors, called district metering areas (DMAs), are expected to meet some requirements and performance criteria such as minimum number of intervention, pressure uniformity, similarity of demands, water quality and number of districts. An efficient methodology to achieve all these requirements together and the proper choice of a criteria governing the sectorization is one of the open questions about optimal DMAs design. This question is addressed in this research by highlighting the advantages of three different criteria when applied to real-word water distribution networks (WDNs). To this, here it is presented a two-stage approach for optimal design of DMAs. The first stage, the clustering of the system, is based on a Louvain-type greedy algorithm for the generalized modularity maximization. The second stage, the physical dividing of the system, is stated as a two-objective optimization problem that utilises the SMOSA version of simulated annealing for multiobjective problems. One objective is the number of isolation valves whereas for the second objective three different performance indices (PIs) are analyzed and compared: (a) standard deviation, (b) Gini coefficient and (c) loss of resilience. The methodology is applied to two real case studies where the first two PIs are optimized to address similar demands among DMAs. The results demonstrate that the proposed method is effective for sectorization into independent DMAs with similar demands. Surprisingly, it found that for the real studied systems, loss of resilience achieves better performance for each district in terms of pressure uniformity and demand similarity than the other two specific performance criteria.
During the last decades, the role of data as a vital resource that enhances decision-making and supports efficient systems operation has become evident, with a growing number of companies viewing data as a key organizational aspects that has to be properly managed, instead of an operational side-product. At the same time, drinking water systems increase in complexity and feature smart sensors, which in turn leads to data-richer operation environments for the water services. Given this challenging context, the often-overlooked factor of ensuring high data quality and preventing errors in data streams becomes increasingly important. In this chapter the current data validation techniques, challenges and best practices of the Dutch drinking water companies is presented.
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During the last decades, the role of data as a vital resource that enhances decision-making and supports efficient systems operation has become evident, with a growing number of companies viewing data as a key organizational aspects that has to be properly managed, instead of an operational side-product. At the same time, drinking water systems increase in complexity and feature smart sensors, which in turn leads to data-richer operation environments for the water services. Given this challenging context, the often-overlooked factor of ensuring high data quality and preventing errors in data streams becomes increasingly important. In this chapter the current data validation techniques, challenges and best practices of the Dutch drinking water companies is presented.
Journal article
(2020)
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Diego Paez, Yves Filion, M.E. Castro Gama, Simone Santopietro, Chris Sweetapple, Fanlin Meng, Raziyeh Farmani, Edo Abraham, Zoran Kapelan, More authors...
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. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.
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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. The effects of damages and repair work were more noticeable during the peak demand periods (morning and noontime) than during the low-flow periods; and tank storage helped to preserve functionality of the network in the first few hours after a simulated event.
Regla de Cobertura Óptima (RCO) de embalses para evitar sequías.
Caso de estudio: Riogrande II, Colombia
En este estudio se presenta una formulación alternativa para la Regla de Cobertura Óptima (RCO) cuyo objetivo es la determinación del la descarga óptima de embalses. Se presenta una función de pérdida de embalse para condiciones de escasez. Dicha función de pérdida de embalse se expresa como función la demanda y almacenamiento requeridos, con respecto del caudal de operación (descarga) y del almacenamiento operacional del embalse, respectivamente. Se presenta la formulación matemática de RCO y se establecen los intervalos de validez. La operación del embalse se realiza mediante un balance de masa (i) Se presenta el caso para el embalse de Riogrande II, Colombia; (ii) se presenta la calibración de la regla de operación estándar (ROE) y de la RCO para periodos mensuales y anuales, y se compara su ajuste de calibración entre observado y simulado; (iii) para el mejor escenario de calibración, se presenta un análisis de sensibilidad de operación para 3 criterios de escasez y 3 criterios de excesos. (iv) Posteriormente la operación calibrada se aleja de los valores mínimos de los seis criterios, se realiza una optimización multi-criterio usando Borg MOEA, y se demuestra de forma teórica la operación óptima de dicho embalse para evitar desabastecimiento o racionamiento en periodos futuros.
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En este estudio se presenta una formulación alternativa para la Regla de Cobertura Óptima (RCO) cuyo objetivo es la determinación del la descarga óptima de embalses. Se presenta una función de pérdida de embalse para condiciones de escasez. Dicha función de pérdida de embalse se expresa como función la demanda y almacenamiento requeridos, con respecto del caudal de operación (descarga) y del almacenamiento operacional del embalse, respectivamente. Se presenta la formulación matemática de RCO y se establecen los intervalos de validez. La operación del embalse se realiza mediante un balance de masa (i) Se presenta el caso para el embalse de Riogrande II, Colombia; (ii) se presenta la calibración de la regla de operación estándar (ROE) y de la RCO para periodos mensuales y anuales, y se compara su ajuste de calibración entre observado y simulado; (iii) para el mejor escenario de calibración, se presenta un análisis de sensibilidad de operación para 3 criterios de escasez y 3 criterios de excesos. (iv) Posteriormente la operación calibrada se aleja de los valores mínimos de los seis criterios, se realiza una optimización multi-criterio usando Borg MOEA, y se demuestra de forma teórica la operación óptima de dicho embalse para evitar desabastecimiento o racionamiento en periodos futuros.
Journal article
(2018)
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Reem F. Digna, Mario E. Castro-Gama, Pieter van der Zaag, Yasir A. Mohamed, Gerald Corzo, Stefan Uhlenbrook
The Eastern Nile Basin is facing a number of transboundary issues, including water resources development, and the associated impacts. The Nile Basin, particularly the Eastern Nile Sub-basin, is considered as one of a few international river systems of potential conflicts between riparian countries. The Eastern Nile is characterized by the high dependency of downstream countries on river water generated in upstream countries, with limited or no contribution to the runoff itself. The aim of this paper is to analyze optimal scenarios for water resources management in the Eastern Nile with regard to hydropower generation and irrigation development. A hydro-economic optimization model based on Genetic Algorithm has been used to determine the maximum benefits for two scenarios: (i) non-cooperative management of hydraulic infrastructure by the riparian countries (status quo), and (ii) cooperative water resources management among the riparian countries. The hydro-economic model is developed using a Genetic Algorithm and deterministic optimization approach covering all hydraulic infrastructures in the Eastern Nile, existing and planned, including the Grand Ethiopian Renaissance Dam (GERD). The results show that cooperative management yields an increase in hydro-energy returns for all countries compared to the status quo, with a very high increase in Ethiopian's returns, as expected. Non-cooperative system management would negatively impact the hydro-energy of Egypt compared to the cooperative management (reduced by 11%), without a significant increase of hydro-energy for Ethiopia. For Sudan, the results show that hydropower generation benefits from the presence of GERD, in both management scenarios. Non-cooperative management of the system, along with the internal trade-off between irrigation and hydropower facilities, would negatively impact irrigation supply in Sudan. The findings support the argument of positive impact of GERD development on the three Eastern Nile riparian countries, Ethiopia, Sudan and Egypt, provided that the three countries agree to manage the system cooperatively.
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The Eastern Nile Basin is facing a number of transboundary issues, including water resources development, and the associated impacts. The Nile Basin, particularly the Eastern Nile Sub-basin, is considered as one of a few international river systems of potential conflicts between riparian countries. The Eastern Nile is characterized by the high dependency of downstream countries on river water generated in upstream countries, with limited or no contribution to the runoff itself. The aim of this paper is to analyze optimal scenarios for water resources management in the Eastern Nile with regard to hydropower generation and irrigation development. A hydro-economic optimization model based on Genetic Algorithm has been used to determine the maximum benefits for two scenarios: (i) non-cooperative management of hydraulic infrastructure by the riparian countries (status quo), and (ii) cooperative water resources management among the riparian countries. The hydro-economic model is developed using a Genetic Algorithm and deterministic optimization approach covering all hydraulic infrastructures in the Eastern Nile, existing and planned, including the Grand Ethiopian Renaissance Dam (GERD). The results show that cooperative management yields an increase in hydro-energy returns for all countries compared to the status quo, with a very high increase in Ethiopian's returns, as expected. Non-cooperative system management would negatively impact the hydro-energy of Egypt compared to the cooperative management (reduced by 11%), without a significant increase of hydro-energy for Ethiopia. For Sudan, the results show that hydropower generation benefits from the presence of GERD, in both management scenarios. Non-cooperative management of the system, along with the internal trade-off between irrigation and hydropower facilities, would negatively impact irrigation supply in Sudan. The findings support the argument of positive impact of GERD development on the three Eastern Nile riparian countries, Ethiopia, Sudan and Egypt, provided that the three countries agree to manage the system cooperatively.
Journal article
(2018)
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Ali D. Abdullah, Mario Erik Castro-Gama, Ioana Popescu, Pieter van der Zaag, Usama Karim, Qusay Al Suhail
Wastewater effluents from irrigation and the domestic and industrial sectors have serious impacts in deteriorating water quality in many rivers, particularly in areas under tidal influence. There is a need to develop an approach that considers the impact of human and natural causes of salinization. This study uses a multi-objective optimization–simulation model to investigate and describe the interactions of such impacts in the Shatt al-Arab River, Iraq. The developed model is able to reproduce the salinity distribution in the river given varying conditions. The salinity regime in the river varies according to different hydrological conditions and anthropogenic activities. Due to tidal effects, salinity caused by drainage water is seen to intrude further upstream into the river. The applied approach provides a way to obtain optimal solutions where both river salinity and deficit in water supply can be minimized. The approach is used for exploring the trade-off between these two objectives.
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Wastewater effluents from irrigation and the domestic and industrial sectors have serious impacts in deteriorating water quality in many rivers, particularly in areas under tidal influence. There is a need to develop an approach that considers the impact of human and natural causes of salinization. This study uses a multi-objective optimization–simulation model to investigate and describe the interactions of such impacts in the Shatt al-Arab River, Iraq. The developed model is able to reproduce the salinity distribution in the river given varying conditions. The salinity regime in the river varies according to different hydrological conditions and anthropogenic activities. Due to tidal effects, salinity caused by drainage water is seen to intrude further upstream into the river. The applied approach provides a way to obtain optimal solutions where both river salinity and deficit in water supply can be minimized. The approach is used for exploring the trade-off between these two objectives.
Journal article
(2017)
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Mario Castro-Gama, Quan Pan, Emilio Attilio Lanfranchi, Andreja Jonoski, Dimitri P. Solomatine
Large water distribution networks require efficient use of their resources. One of the ways to become more efficient is to reduce the energy consumption due to pumping systems [1] [2]. In the European context the city of Milan has a large water supply system for 1.3 million inhabitants and around 4.0 million commuters, which is supplied entirely by 26 pumping stations. The system currently supplies its ∼50,000 customers with 103 pumps which are actively operated during the day [3]. In previous years a pump scheduling algorithm has been proposed to the utility for a Pressure Management Zone (PMZ) in the south of the city named Abbiategrasso containing only 4 pumps [4] [5]. However, it is of the interest for the utility to extend the analysis to the whole system [6] [7]. For that reason it is necessary to perform a proper pump scheduling. The solution proposed here, is a Multi-Objective Optimization (MOO) for the energy consumption reduction of the whole Water Distribution Network (WDN) using an EPANET model of the whole network. Results show that there is room for improvement of energy and pressure management in the system. The solution presented here can be applied to other utilities with similar challenges.
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Large water distribution networks require efficient use of their resources. One of the ways to become more efficient is to reduce the energy consumption due to pumping systems [1] [2]. In the European context the city of Milan has a large water supply system for 1.3 million inhabitants and around 4.0 million commuters, which is supplied entirely by 26 pumping stations. The system currently supplies its ∼50,000 customers with 103 pumps which are actively operated during the day [3]. In previous years a pump scheduling algorithm has been proposed to the utility for a Pressure Management Zone (PMZ) in the south of the city named Abbiategrasso containing only 4 pumps [4] [5]. However, it is of the interest for the utility to extend the analysis to the whole system [6] [7]. For that reason it is necessary to perform a proper pump scheduling. The solution proposed here, is a Multi-Objective Optimization (MOO) for the energy consumption reduction of the whole Water Distribution Network (WDN) using an EPANET model of the whole network. Results show that there is room for improvement of energy and pressure management in the system. The solution presented here can be applied to other utilities with similar challenges.
Decision support systems (DSS) have been wildly developed in the recent decades, in various areas of decision making. In the 21st century, the advances in Information and Communication Technology (ICT) have brought the era of cloud computing, in which network-distributed resources (simulation and optimization models, data, etc.) are integrated in decision support applications. The aim of the present article is to present the application of web-based decision support systems (WBDSS) in the area of water supply networks (WSN). A simplified method to integrate ICT solutions, comprising two multi-objective optimization algorithms, and one hydraulic simulation model, into one WBDSS is described. Details of the architecture, implementation, and the perspective of future development are addressed. The WBDSS is developed for one particular case study that represents one zone of the water distribution network of city of Milan in Italy. This zone, named Abbiategrasso pilot zone, is supplied by pumped water, and has been isolated from the rest of the water distribution network for purposes of testing new operational strategies, leading to increased energy and water efficiency and improved pressure management. The WBDSS has been developed and applied in this zone for pump scheduling optimization. Although the focus of the article is on WBDSS, selected results from this optimization are also presented. This research is part of the ICeWater project, which is funded by EU FP7 Programme.
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Decision support systems (DSS) have been wildly developed in the recent decades, in various areas of decision making. In the 21st century, the advances in Information and Communication Technology (ICT) have brought the era of cloud computing, in which network-distributed resources (simulation and optimization models, data, etc.) are integrated in decision support applications. The aim of the present article is to present the application of web-based decision support systems (WBDSS) in the area of water supply networks (WSN). A simplified method to integrate ICT solutions, comprising two multi-objective optimization algorithms, and one hydraulic simulation model, into one WBDSS is described. Details of the architecture, implementation, and the perspective of future development are addressed. The WBDSS is developed for one particular case study that represents one zone of the water distribution network of city of Milan in Italy. This zone, named Abbiategrasso pilot zone, is supplied by pumped water, and has been isolated from the rest of the water distribution network for purposes of testing new operational strategies, leading to increased energy and water efficiency and improved pressure management. The WBDSS has been developed and applied in this zone for pump scheduling optimization. Although the focus of the article is on WBDSS, selected results from this optimization are also presented. This research is part of the ICeWater project, which is funded by EU FP7 Programme.
Along with nowadays growth of urban areas and population, it is more and more important to have better water resources management, especially regarding drinking water supply. Maintaining a good state of a water distribution network poses challenges that are addressed by research community. Two of the main challenges in management of water distribution systems are the reduction of energy consumption due to the high pumping requirements in some systems and/or reduction of water losses. European Commission is encouraging research in this area and currently has funded the EU FP7 project ICe WATER, that aims at development of new ICT strategies for management and operation of water supply systems. Present article focuses on the presentation of the solution for reducing energy consumption, as it was proposed within the project. The solution is applicable to any water distribution system; therefore the principles and methodology demonstrated herein are general.
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Along with nowadays growth of urban areas and population, it is more and more important to have better water resources management, especially regarding drinking water supply. Maintaining a good state of a water distribution network poses challenges that are addressed by research community. Two of the main challenges in management of water distribution systems are the reduction of energy consumption due to the high pumping requirements in some systems and/or reduction of water losses. European Commission is encouraging research in this area and currently has funded the EU FP7 project ICe WATER, that aims at development of new ICT strategies for management and operation of water supply systems. Present article focuses on the presentation of the solution for reducing energy consumption, as it was proposed within the project. The solution is applicable to any water distribution system; therefore the principles and methodology demonstrated herein are general.