Knudsen, J., Bendtsen, J.D., Andersen, P. et al. (3 more authors) (2017) Fuel Optimization in Multiple Diesel Driven Generator Power Plants. In: 2017 IEEE Conference on Control Technology and Applications (CCTA). 2017 IEEE Conference on Control Technology and Applications, 27-30 Aug 2017, Kohala Coast, Hawai'i. Institute of Electrical and Electronics Engineers ISBN 978-1-5090-2182-6
Abstract
This paper presents two fuel optimization approaches for independent power producer (IPP) power plants consisting of multiple diesel driven generator sets (DGs). The optimization approaches utilize assumed information about the fuel consumption characteristics of each DG in an effort to demonstrate the potential benefits of acquiring such information. Reasonable variations in fuel consumption characteristics are based on measurements of a DG during restricted air filter flow operation. The two approaches are: (i) a gradient search approach capable of finding the optimal power generation for each DG in a fixed selection of DGs accommodating a given plant power reference and (ii) a genetic algorithm approach further capable of determining the optimal selection of DGs to operate in an IPP power plant. Both approaches show notable potential benefits, in terms of fuel savings, compared to current market-leading solutions.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2017 IEEE. This is an author produced version of a paper subsequently published in 2017 IEEE Conference on Control Technology and Applications (CCTA). Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 May 2017 10:52 |
Last Modified: | 15 Mar 2018 14:59 |
Published Version: | https://doi.org/10.1109/CCTA.2017.8062510 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/CCTA.2017.8062510 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116481 |