Optimising Pump Scheduling for Water Distribution Networks

Zhao, Y; Liang, B; Wang, Y; Dang, S; Taib, R; Chen, F; Hua, T; Vitanage, D; Doolan, C

Optimising Pump Scheduling for Water Distribution Networks

Zhao, Y Liang, B

Wang, Y Dang, S Taib, R Chen, F

Hua, T Vitanage, D Doolan, C

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, 11919 LNAI, pp. 433-444
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Zhao, Y
dc.contributor.author	Liang, B https://orcid.org/0000-0002-6605-2167
dc.contributor.author	Wang, Y
dc.contributor.author	Dang, S
dc.contributor.author	Taib, R
dc.contributor.author	Chen, F https://orcid.org/0000-0003-4971-8729
dc.contributor.author	Hua, T
dc.contributor.author	Vitanage, D
dc.contributor.author	Doolan, C
dc.date.accessioned	2020-06-11T08:11:50Z
dc.date.available	2020-06-11T08:11:50Z
dc.date.issued	2019-01-01
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, 11919 LNAI, pp. 433-444
dc.identifier.isbn	9783030352875
dc.identifier.issn	0302-9743
dc.identifier.issn	1611-3349
dc.identifier.uri	http://hdl.handle.net/10453/141367
dc.description.abstract	© 2019, Springer Nature Switzerland AG. Energy costs can be a major component of operational costs for water utilities. Operational efficiencies including optimising energy costs while maintaining continuity of supply is one area to reduce overall operational costs. To address the challenge, we have proposed an effective optimisation model to minimise the energy cost for water distribution networks. A simulation of the model over a water distribution network in Sydney demonstrated that 15% saving in energy cost could be achieved using this approach, as compared with the existing rule-based method.
dc.language	en
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.isbasedon	10.1007/978-3-030-35288-2_35
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Optimising Pump Scheduling for Water Distribution Networks
dc.type	Conference Proceeding
utslib.citation.volume	11919 LNAI
utslib.for	0801 Artificial Intelligence and Image Processing
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/A/DRsch The Data Science Institute
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2020-06-11T08:11:45Z
pubs.publication-status	Published
pubs.volume	11919 LNAI

Abstract:

© 2019, Springer Nature Switzerland AG. Energy costs can be a major component of operational costs for water utilities. Operational efficiencies including optimising energy costs while maintaining continuity of supply is one area to reduce overall operational costs. To address the challenge, we have proposed an effective optimisation model to minimise the energy cost for water distribution networks. A simulation of the model over a water distribution network in Sydney demonstrated that 15% saving in energy cost could be achieved using this approach, as compared with the existing rule-based method.

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http://hdl.handle.net/10453/141367