Mapping and Modeling Interdependent Power, Water, and Gas Infrastructures

Momeni, Ahmad; Prasad, Vindhyawasini; Dharmawardena, Hasala; Piratla, Kalyan R.; Venayagamoorthy, G.K.

doi:10.1109/psc.2018.8664050

Cited by 8 publications

(6 citation statements)

References 58 publications

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“…A hydraulicmodel-based scheme for leakage detection and most importantly severity assessment could offer promise given the growing adoption of smart water meters and continuous hydraulic monitoring of WDSs. As a result, building upon previous studies (Momeni et al, 2018(Momeni et al, , 2020Piratla and Momeni, 2019;Momeni and Piratla, 2021), this paper (i) offers a preliminary proofof-concept study of a fully data-driven hydraulic model-based prediction paradigm leveraging pressure monitoring data where not only are leak sources detected, but also their severities captured with a reasonable accuracy and (ii) conducts a series of sensitivity analyses of the very prediction model to the number and placement of smart meters and pressure monitoring stations. This preliminary study proves novel by shedding light on a wider scope of how consumption data can be leveraged to minimize the risk of major pipe breaks due to difficult-to-detect leaks without entirely relying on manual inspection techniques and consequently imposing less maintenance costs on municipalities.…”

Section: Introductionmentioning

confidence: 94%

“…As the increasing paucity of water resources and the fast-growing water demands (Gupta and Kulat, 2018) in water distribution systems (WDSs) as a critical infrastructure in societies loom ahead, sustainable maintenance of WDSs operationally and financially is of an utmost essence (Gupta and Kulat, 2018;Momeni et al, 2018;Zhang K. et al, 2019;Al Qahtani et al, 2020;Shukla and Piratla, 2020). Specifically, leakage in WDSs reportedly makes up between 5 and 50 percent of the total freshwater losses depending on the conditions of the pipelines in developed countries (Gupta and Kulat, 2018;Sophocleous et al, 2019;Shukla and Piratla, 2020;Yazdekhasti et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

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A Proof-of-Concept Study for Hydraulic Model-Based Leakage Detection in Water Pipelines Using Pressure Monitoring Data

Momeni¹,

Piratla²

2021

Front. Water

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It is estimated that about 20% of treated drinking water is lost through distribution pipeline leakages in the United States. Pipeline leakage detection is a top priority for water utilities across the globe as leaks increase operational energy consumption and could also develop into potentially catastrophic water main breaks, if left unaddressed. Leakage detection is a laborious task often limited by the financial and human resources that utilities can afford. Many conventional leak detection techniques also only offer a snapshot indication of leakage presence. Furthermore, the reliability of many leakage detection techniques on plastic pipelines that are increasingly preferred for drinking water applications is questionable. As part of a smart water utility framework, this paper proposes and validates a hydraulic model-based technique for detecting and assessing the severity of leakages in buried water pipelines through monitoring of pressure from across the water distribution system (WDS). The envisioned smart water utility framework entails the capabilities to collect water consumption data from a limited number of WDS nodes and pressure data from a limited number of pressure monitoring stations placed across the WDS. A popular benchmark WDS is initially modified by inducing leakages through addition of orifice nodes. The leakage severity is controlled using emitter coefficients of the orifice nodes. WDS pressure data for various sets of demands is subsequently gathered from locations where pressure monitoring stations are to be placed in that modified distribution network. An evolutionary optimization algorithm is subsequently used to predict the emitter coefficients so as to determine the leakage severities based on the hydraulic dependency of the monitored pressure data on various sets of nodal demands. Artificial neural networks (ANNs) are employed to mimic the popular hydraulic solver EPANET 2.2 for high computational efficiency. The goals of this study are to: (1) validate the proof of concept of the proposed modeling approach for detecting and assessing the severity of leakages and (2) evaluate the sensitivity of the prediction accuracy to number of pressure monitoring stations and number of demand nodes at which consumption data is gathered and used. This study offers new value to prioritize pipes for rehabilitation by predicting leakages through a hydraulic model-based approach.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

A Proof-of-Concept Study for Hydraulic Model-Based Leakage Detection in Water Pipelines Using Pressure Monitoring Data

Momeni¹,

Piratla²

2021

Front. Water

Self Cite

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show abstract

“…the empirical methods, cannot capture the impacts of system failure, while others, e.g. the economic theory methods, cannot function at a component level (Momeni et al, 2018) which can be problematic when simulating AD performance in this study. The flowbased method can provide an accurate model framework when implemented with high temporal resolution, but this may be computationally expensive (Momeni et al, 2018).…”

Section: Agent-based Modelling (Abm)mentioning

confidence: 99%

“…System Dynamics or ABM techniques can be used in this study as they can quantify the cascading effects (Iturriza et al, 2018). The System Dynamics method has a reputation of being reliable in analysing complex interdependent systems (Zio and Sansavini, 2011), but it requires calibration (Momeni et al, 2018), which may prove challenging to achieve in this study due to the lack of data.…”

Section: Agent-based Modelling (Abm)mentioning

confidence: 99%

“…Accounting for future uncertainties can be accomplished through ABM by considering a range of input parameter values and employing the Monte Carlo method to produce a range of potential outputs. Whilst the main disadvantage of the ABM approach is the demand for large datasets, this problem is common with most methods (Momeni et al, 2018), and its consequences can be mitigated by making realistic assumptions, when needed, based on expert knowledge.…”

Section: Agent-based Modelling (Abm)mentioning

confidence: 99%

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Modelling the diffusion and operation of anaerobic digestions in Great Britain under future scenarios within the scope of water-energy-food nexus

Abdel-Aal

Haltaş

Varga

2020

Journal of Cleaner Production

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The paper aims to understand the impacts of the spatial and temporal diffusion of Anaerobic Digestion (AD) on the Water Energy Food (WEF) nexus and to quantify the associated environmental, social and economic benefits. Contemporary tight carbon reduction targets urge the need to deploy renewable energy technologies however due to interdependencies across the WEF nexus, various technologies are beneficial for some but not all sectors. This paper quantifies the impacts of future possible AD technology diffusion choices on the environment, society and economy. This can aid decision makers to identify the potential consequences of various AD alternatives within the next three decades. The study considers an integrated WEF nexus approach and accounts for the interdependencies within the nexus. This was done by developing an Agent-Based Model (ABM) and simulating the relations between the main players within the nexus, thus examining the upscaling of AD diffusion and its consequences for water consumption, energy production, transportation, landfill use, food waste processing and digestate generation. Three future WEF nexus scenarios, that reflect potential alternatives of society and technology in Great Britain up to 2050, were utilised by the ABM implementation to test the sensitivity of AD diffusion choices. These scenarios describe possible changes to lifestyle, governance, technologies, climate, and social structures. Accounting for the uncertainty associated with such future simulations, the Monte Carlo method was employed to estimate the potential variations in scenario outputs. Results suggest that decentralisation results in the largest carbon reduction, but can incur more costs. Centralisation consumes 35% more water but produces 37% more energy (biogas). The paper has visualised the scenario outputs graphically to highlight the consequences of neglecting the inter-relationships between environmental, social and economic aspects of AD.

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An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies

Al-Zarooni

Bashir

2020

Int J Syst Assur Eng Manag

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Mapping and Modeling Interdependent Power, Water, and Gas Infrastructures

Cited by 8 publications

References 58 publications

A Proof-of-Concept Study for Hydraulic Model-Based Leakage Detection in Water Pipelines Using Pressure Monitoring Data

A Proof-of-Concept Study for Hydraulic Model-Based Leakage Detection in Water Pipelines Using Pressure Monitoring Data

Modelling the diffusion and operation of anaerobic digestions in Great Britain under future scenarios within the scope of water-energy-food nexus

An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies

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