Model-based methodology for the design of optimal control strategies in MBR plants
Autores: Sergio Beltrán Montse Dalmau Luis Sancho Joaquim Comas Ignasi Rodríguez-Roda Eduardo Ayesa
Fecha: 16.06.2017
Water Science & Technology
Abstract
This paper proposes a model-based methodology that allows synthesizing the most appropriate strategies for optimising the operation of wastewater treatment plants. The methodology is applied with the aim of maximising the nitrogen removal in membrane bioreactors. The proposed procedure is based on a systematic approach composed by four steps. First, a sensitivity analysis of the input variables is carried out in order to obtain a first assessment of the potential for operational improvements. Then, the optimum input variables values are calculated by a model-based optimisation algorithm that minimises a cost function associated with the effluent total nitrogen at different temperatures. Then, the optimum operational strategies are identified. Finally, these operational strategies are the conceptual knowledge base for designing automatic control laws. The obtained optimal control strategies have shown a significant improvement of performance in comparison with a fixed operation for the studied case, decreasing the total nitrogen by 40%.
BIB_text
title = {Model-based methodology for the design of optimal control strategies in MBR plants},
journal = {Water Science & Technology},
pages = {2546-2553},
number = {11},
volume = {75},
keywds = {
optimisation; WWTP; operation; model-based; MBR
}
abstract = {
This paper proposes a model-based methodology that allows synthesizing the most appropriate strategies for optimising the operation of wastewater treatment plants. The methodology is applied with the aim of maximising the nitrogen removal in membrane bioreactors. The proposed procedure is based on a systematic approach composed by four steps. First, a sensitivity analysis of the input variables is carried out in order to obtain a first assessment of the potential for operational improvements. Then, the optimum input variables values are calculated by a model-based optimisation algorithm that minimises a cost function associated with the effluent total nitrogen at different temperatures. Then, the optimum operational strategies are identified. Finally, these operational strategies are the conceptual knowledge base for designing automatic control laws. The obtained optimal control strategies have shown a significant improvement of performance in comparison with a fixed operation for the studied case, decreasing the total nitrogen by 40%.
}
pubmed = {1},
doi = {10.2166/wst.2017.135},
date = {2017-06-16},
year = {2017},
}
