Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process

Peter Alexander Stentoft, Thomas Munk-Nielsen, Peter Steen Mikkelsen, Henrik Madsen, Luca Vezzaro, Jan Kloppenborg Møller

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Abstract

Wastewater treatment aeration accounts for a large amount of societal electricity consumption. This abstract suggests MPC driven by stochastic differential equations and genetic optimization, under legal and equipment constraints to prioritize aeration in selected periods. Thereby we reduce costs and empower smart use of green electricity from e.g. wind turbines.
Original languageEnglish
Title of host publicationProceedings of 6th IFAC Conference on Nonlinear Model Predictive Control
Number of pages2
PublisherInternational Federation of Automatic Control
Publication date2018
Article numberMoAPo1.30
Publication statusPublished - 2018
Event6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018) - Madison, United States
Duration: 19 Aug 2018 → 22 Aug 2018

Conference

Conference6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018)
CountryUnited States
CityMadison
Period19/08/2018 → 22/08/2018

Keywords

  • Stochastic Systems
  • Genetic Algorithms
  • Process Control
  • Predictive Control
  • Water Pollution
  • Smart Power Applications

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    Cite this

    Stentoft, P. A., Munk-Nielsen, T., Mikkelsen, P. S., Madsen, H., Vezzaro, L., & Møller, J. K. (2018). Smart Power, Cost-Effective MPC of Stochastic Wastewater Treatment Process. In Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control [MoAPo1.30] International Federation of Automatic Control.