Pournaras, E, Taormina, R, Thapa, M et al. (3 more authors) (2020) Cascading Failures in Interconnected Power-to-Water Networks. ACM SIGMETRICS Performance Evaluation Review, 47 (4). pp. 16-20. ISSN 0163-5999
Abstract
The manageability and resilience of critical infrastructures, such as power and water networks, is challenged by their increasing interdependence and interconnectivity. Power networks often experience cascading failures, i.e. blackouts, that have unprecedented economic and social impact. Al- though knowledge exists about how to control such complex non-linear phenomena within a single power network, little is known about how such failures can spread and coevolve in the water network when failing power components energize the water distribution infrastructure, i.e. pumps and valves. This paper studies such a scenario and specifically the impact of power cascading failures on shortages of water supply. A realistic exemplary of an interconnected power-to-water network is experimentally evaluated using a modular simulation approach. Power and waterflow dynamics are simulated separately by taking into account different maximum powerlines capacities and water demand requirements. Results showcase the strong dependency of urban water sup- ply systems on the reliability of power networks, with severe shortages of water supply being caused by failures originating indistant power lines, especially for heavily loaded power networks.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright is held by author/owner(s). This is an author produced version of a journal article published in ACM SIGMETRICS Performance Evaluation Review. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Sep 2020 14:58 |
Last Modified: | 29 Sep 2020 14:58 |
Status: | Published |
Publisher: | Association for Computing Machinery (ACM) |
Identification Number: | 10.1145/3397776.3397781 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165735 |