Uncertainty reduction in integrated control: Confronting model predictions with information from on-line data
(2005) 2nd IWA Conference on Instrumentation, Control and Automation (ICA2005)- Abstract
- Over the past 10-15 years WWTP control system performance has improved
significantly by increased usage of on-line WWTP data. It is now time to extend
the intensive use of on-line data to the sewer system, where on-line data can be
used within control of both sewer and WWTP. A generic methodology for
exploiting on-line sewer system data - as discussed in this paper - have revealed
that these data seem as useful for good control as on-line WWTP data. Also, the
integrated approach where sewer data are used for WWTP control and vice versa
has proven successful and valuable. The critical step in using on-line sewer
system data is to select sufficiently efficient methods... (More) - Over the past 10-15 years WWTP control system performance has improved
significantly by increased usage of on-line WWTP data. It is now time to extend
the intensive use of on-line data to the sewer system, where on-line data can be
used within control of both sewer and WWTP. A generic methodology for
exploiting on-line sewer system data - as discussed in this paper - have revealed
that these data seem as useful for good control as on-line WWTP data. Also, the
integrated approach where sewer data are used for WWTP control and vice versa
has proven successful and valuable. The critical step in using on-line sewer
system data is to select sufficiently efficient methods for data reduction and
information extraction. An approach to this is proposed, where on-line data are
evaluated to distinguish between the stable dry weather situations and clear rain
situations. This approach allows a fast identification of the catchment area and
rainflows, for example in pumping stations. The use of the developed methods
indicates that PST data provide more reliable information on the actual rain
distribution than rain gauges. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/641663
- author
- Nielsen, M K ; Lindstrøm, M ; Gernaey, K V and Madsen, H
- publishing date
- 2005
- type
- Contribution to conference
- publication status
- published
- subject
- conference name
- 2nd IWA Conference on Instrumentation, Control and Automation (ICA2005)
- conference dates
- 2005-05-29 - 2005-06-02
- language
- English
- LU publication?
- no
- additional info
- Invited paper
- id
- c45dc07c-a7ab-485b-b17f-b847c349a0f1 (old id 641663)
- date added to LUP
- 2016-04-04 14:06:48
- date last changed
- 2018-11-21 21:18:21
@misc{c45dc07c-a7ab-485b-b17f-b847c349a0f1,
abstract = {{Over the past 10-15 years WWTP control system performance has improved<br/><br>
significantly by increased usage of on-line WWTP data. It is now time to extend<br/><br>
the intensive use of on-line data to the sewer system, where on-line data can be<br/><br>
used within control of both sewer and WWTP. A generic methodology for<br/><br>
exploiting on-line sewer system data - as discussed in this paper - have revealed<br/><br>
that these data seem as useful for good control as on-line WWTP data. Also, the<br/><br>
integrated approach where sewer data are used for WWTP control and vice versa<br/><br>
has proven successful and valuable. The critical step in using on-line sewer<br/><br>
system data is to select sufficiently efficient methods for data reduction and<br/><br>
information extraction. An approach to this is proposed, where on-line data are<br/><br>
evaluated to distinguish between the stable dry weather situations and clear rain<br/><br>
situations. This approach allows a fast identification of the catchment area and<br/><br>
rainflows, for example in pumping stations. The use of the developed methods<br/><br>
indicates that PST data provide more reliable information on the actual rain<br/><br>
distribution than rain gauges.}},
author = {{Nielsen, M K and Lindstrøm, M and Gernaey, K V and Madsen, H}},
language = {{eng}},
title = {{Uncertainty reduction in integrated control: Confronting model predictions with information from on-line data}},
year = {{2005}},
}