Approximation of System Components for Pump Scheduling Optimisation
File(s)
Published version
Author(s)
Menke, R
Abraham, E
Parpas, P
Stoianov, I
Type
Conference Paper
Abstract
The operation of pump systems in water distribution systems (WDS) is commonly the most expensive task for utilities with up
to 70% of the operating cost of a pump system attributed to electricity consumption. Optimisation of pump scheduling could save
10-20% by improving efficiency or shifting consumption to periods with low tariffs.
Due to the complexity of the optimal control problem, heuristic methods which cannot guarantee optimality are often applied.
To facilitate the use of mathematical optimisation this paper investigates formulations of WDS components. We show that linear
approximations outperform non-linear approximations, while maintaining comparable levels of accuracy.
to 70% of the operating cost of a pump system attributed to electricity consumption. Optimisation of pump scheduling could save
10-20% by improving efficiency or shifting consumption to periods with low tariffs.
Due to the complexity of the optimal control problem, heuristic methods which cannot guarantee optimality are often applied.
To facilitate the use of mathematical optimisation this paper investigates formulations of WDS components. We show that linear
approximations outperform non-linear approximations, while maintaining comparable levels of accuracy.
Date Issued
2015-09-01
Date Acceptance
2015-07-02
Citation
Procedia Engineering, 2015, 119, pp.1059-1068
ISSN
1877-7058
Publisher
Elsevier
Start Page
1059
End Page
1068
Journal / Book Title
Procedia Engineering
Volume
119
Copyright Statement
© 2015 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND licence http://creativecommons.org/licenses/by-nc-nd/4.0/
This is an open access article under the CC BY-NC-ND licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Source
Proc. 13th Int. Conference on Computing and Control in the Water Industry (CCWI)
Publication Status
Published
Start Date
2015-09-02
Finish Date
2015-09-04
Coverage Spatial
De Montfort University, UK