Adaptive model based control for wastewater treatment plants

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Abstract

In biological wastewater treatment, nitrogen and phosphorous are removed by activated sludge. The process requires oxygen input via aeration of the activated sludge tank. Aeration is responsible for about 60% of the energy consumption of a treatment plant. Hence optimization of aeration can contribute considerably to the increase of energy-efficiency in wastewater treatment. To this end, we introduce an adaptive model based control strategy for aeration called adaptive WOMBAT. The strategy is an improvement of the original WOMBAT, which has been successfully implemented at wastewater treatment plant Westpoort in Amsterdam. In this paper we propose to improve the physics-based model by introducing automatic parameter adaptation. In an experimental model setup the adaptive model based control algorithm proves to result in better effluent quality with less energy consumption. Moreover, it is able to react to the varying circumstances of a real treatment plant and can, therefore, operate without human supervision.
Original languageUndefined
Title of host publicationUrban Water Management: Callenges and Opportunities. Proceedings of the Eleventh International Conference on Computing and Control for the Water Industry (CCWI 2011)
EditorsD.A. Savic, Z. Kapelan, D. Butler
Place of PublicationExeter
PublisherExeter University
Pages683-688
Number of pages6
ISBN (Print)0-9539140-8-9
Publication statusPublished - 2011

Publication series

Name
PublisherExeter University

Keywords

  • METIS-281532
  • Model based control
  • Adaptive control
  • Aeration
  • EWI-20495
  • Optimization
  • Wastewater treatment
  • Energy Efficiency
  • IR-78387

Cite this

de Niet, A., van de Vrugt, N. M., Korving, H., & Boucherie, R. J. (2011). Adaptive model based control for wastewater treatment plants. In D. A. Savic, Z. Kapelan, & D. Butler (Eds.), Urban Water Management: Callenges and Opportunities. Proceedings of the Eleventh International Conference on Computing and Control for the Water Industry (CCWI 2011) (pp. 683-688). Exeter: Exeter University.