Management of compressed air to reduce energy consumption using intelligent systems

Mohamad Thabet; David Sanders; Malik Haddad; Nils Bausch; Giles Tewkesbury; Victor Becerra; Tom Barker; Jake Piner

doi:10.1007/978-3-030-55190-2_16

Management of compressed air to reduce energy consumption using intelligent systems

Mohamad Thabet, David Sanders, Malik Haddad, Nils Bausch, Giles Tewkesbury, Victor Becerra, Tom Barker, Jake Piner

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

173 Downloads (Pure)

Abstract

This research investigated the use of intelligent systems for reducing energy consumption in compressed air systems. An initial literature review has been completed and mathematical models that describe typical compressed air components (compressor, tank, piping network, etc.) were created. The investigations suggested that energy used or wasted in connection with compressed air was a valuable research area to attempt to save energy. The research progressed to investigating ways of minimising energy use for air compressors based on real-time conditions (including anticipated future requirements), using intelligent systems to monitor and make decisions.

Original language	English
Title of host publication	Intelligent Systems and Applications
Subtitle of host publication	Volume 3
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Publisher	Springer
Pages	206-217
ISBN (Electronic)	978-3-030-55190-2
ISBN (Print)	978-3-030-55189-6
DOIs	https://doi.org/10.1007/978-3-030-55190-2_16
Publication status	Published - 25 Aug 2020
Event	Intelligent Systems Conference - London, United Kingdom Duration: 3 Sept 2020 → 4 Sept 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	1252
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Intelligent Systems Conference
Abbreviated title	IntelliSys 2020
Country/Territory	United Kingdom
City	London
Period	3/09/20 → 4/09/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-55190-2_16

Management of Compressed Air
This is a post-peer-review, pre-copyedit version of an article published in Advances in Intelligent Systems and Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-55190-2_16.
Accepted author manuscript (Post-print), 326 KB

COFUND / DTA3 Marie Skłodowska-Curie PhD Fellowship "Making decisions about saving energy in Compressed Air Systems using Ambient Intelligence and AI"
Sanders, D., Tewkesbury, G. & Bausch, N.
1/04/19 → 31/03/22
Project: Research

File
DTA3/Cofund Marie Skłodowska-curie Phd Fellowship Programme
Becerra, V.
1/10/18 → 30/09/21
Project: Research
Management and Business Decision Making
Haddad, M. & Sanders, D.
26/09/16 → 29/04/22
Project: Research

Top two per cent of researchers in the world
Sanders, David (Recipient), 2 Nov 0001
Prize: National/international honour

Cite this

Thabet, M., Sanders, D., Haddad, M., Bausch, N., Tewkesbury, G., Becerra, V., Barker, T., & Piner, J. (2020). Management of compressed air to reduce energy consumption using intelligent systems. In K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Systems and Applications: Volume 3 (pp. 206-217). (Advances in Intelligent Systems and Computing; Vol. 1252). Springer. https://doi.org/10.1007/978-3-030-55190-2_16

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title = "Management of compressed air to reduce energy consumption using intelligent systems",

abstract = "This research investigated the use of intelligent systems for reducing energy consumption in compressed air systems. An initial literature review has been completed and mathematical models that describe typical compressed air components (compressor, tank, piping network, etc.) were created. The investigations suggested that energy used or wasted in connection with compressed air was a valuable research area to attempt to save energy. The research progressed to investigating ways of minimising energy use for air compressors based on real-time conditions (including anticipated future requirements), using intelligent systems to monitor and make decisions.",

author = "Mohamad Thabet and David Sanders and Malik Haddad and Nils Bausch and Giles Tewkesbury and Victor Becerra and Tom Barker and Jake Piner",

year = "2020",

month = aug,

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doi = "10.1007/978-3-030-55190-2_16",

language = "English",

isbn = "978-3-030-55189-6",

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editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",

booktitle = "Intelligent Systems and Applications",

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}

Thabet, M, Sanders, D, Haddad, M, Bausch, N, Tewkesbury, G , Becerra, V, Barker, T & Piner, J 2020, Management of compressed air to reduce energy consumption using intelligent systems. in K Arai, S Kapoor & R Bhatia (eds), Intelligent Systems and Applications: Volume 3. Advances in Intelligent Systems and Computing, vol. 1252, Springer, pp. 206-217, Intelligent Systems Conference, London, United Kingdom, 3/09/20. https://doi.org/10.1007/978-3-030-55190-2_16

Management of compressed air to reduce energy consumption using intelligent systems. / Thabet, Mohamad; Sanders, David; Haddad, Malik et al.
Intelligent Systems and Applications: Volume 3. ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Springer, 2020. p. 206-217 (Advances in Intelligent Systems and Computing; Vol. 1252).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Management of compressed air to reduce energy consumption using intelligent systems

AU - Thabet, Mohamad

AU - Sanders, David

AU - Haddad, Malik

AU - Bausch, Nils

AU - Tewkesbury, Giles

AU - Becerra, Victor

AU - Barker, Tom

AU - Piner, Jake

PY - 2020/8/25

Y1 - 2020/8/25

N2 - This research investigated the use of intelligent systems for reducing energy consumption in compressed air systems. An initial literature review has been completed and mathematical models that describe typical compressed air components (compressor, tank, piping network, etc.) were created. The investigations suggested that energy used or wasted in connection with compressed air was a valuable research area to attempt to save energy. The research progressed to investigating ways of minimising energy use for air compressors based on real-time conditions (including anticipated future requirements), using intelligent systems to monitor and make decisions.

AB - This research investigated the use of intelligent systems for reducing energy consumption in compressed air systems. An initial literature review has been completed and mathematical models that describe typical compressed air components (compressor, tank, piping network, etc.) were created. The investigations suggested that energy used or wasted in connection with compressed air was a valuable research area to attempt to save energy. The research progressed to investigating ways of minimising energy use for air compressors based on real-time conditions (including anticipated future requirements), using intelligent systems to monitor and make decisions.

U2 - 10.1007/978-3-030-55190-2_16

DO - 10.1007/978-3-030-55190-2_16

M3 - Conference contribution

SN - 978-3-030-55189-6

T3 - Advances in Intelligent Systems and Computing

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EP - 217

BT - Intelligent Systems and Applications

A2 - Arai, Kohei

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Management of compressed air to reduce energy consumption using intelligent systems

Abstract

Publication series

Conference

UN SDGs

Access to Document

Fingerprint

Projects

COFUND / DTA3 Marie Skłodowska-Curie PhD Fellowship "Making decisions about saving energy in Compressed Air Systems using Ambient Intelligence and AI"

DTA3/Cofund Marie Skłodowska-curie Phd Fellowship Programme

Management and Business Decision Making

Prizes

Top two per cent of researchers in the world

Cite this