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.
|Title of host publication||Proceedings of 6th IFAC Conference on Nonlinear Model Predictive Control|
|Number of pages||2|
|Publisher||International Federation of Automatic Control|
|Publication status||Published - 2018|
|Event||6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018) - Madison, United States|
Duration: 19 Aug 2018 → 22 Aug 2018
|Conference||6th IFAC Conference on Nonlinear Model Predictive Control (NMPC 2018)|
|Period||19/08/2018 → 22/08/2018|
- Stochastic Systems
- Genetic Algorithms
- Process Control
- Predictive Control
- Water Pollution
- Smart Power Applications
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.