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Conference paper

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

In Proceedings of 6th Ifac Conference on Nonlinear Model Predictive Control — 2018

By Stentoft, Peter Alexander1,2; Munk-Nielsen, Thomas3; Mikkelsen, Peter Steen4,5; Madsen, Henrik1,2; Vezzaro, Luca4,5; Møller, Jan Kloppenborg1,2

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Dynamical Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Krüger Veolia Water Technologies3

Urban Water Systems, Department of Environmental Engineering, Technical University of Denmark4

Department of Environmental Engineering, Technical University of Denmark5

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.

Language: English
Publisher: International Federation of Automatic Control
Year: 2018
Proceedings: 6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018)
Types: Conference paper
ORCIDs: Stentoft, Peter Alexander , Mikkelsen, Peter Steen , Madsen, Henrik , Vezzaro, Luca and Møller, Jan Kloppenborg
Keywords

Genetic Algorithms Predictive Control Process Control SDG 7 - Affordable and Clean Energy Smart Power Applications Stochastic Systems Water Pollution

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