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A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor
Abstract
This paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure. Further, it presents the introduction of an optimisation layer for the structure and parameters of the SBR cycle, through the synthesis of stochastic methods: single-objective optimisation (SOO) using a genetic algorithm (GA) and multi-objective optimisation (MOO) using the NSGA-II algorithm. The results were compared to a classical approach with fixed cycle parameters. The paper shows the advantages of optimising cycle parameters, including the number of phases as well as the DO value, on the process flow. These control structures underwent simulation tests in the MATLAB environment with the Simba package. The biochemical processes occurring in the reactor are based on the Activated Sludge Model No. 2d (ASM2d). The optimising control system demonstrates tangible improvements in operational efficiency and significant reductions in electrical energy consumption, highlighting the effectiveness of the proposed methodologies. © 2017 Elsevier Inc. All rights reserved.
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
JOURNAL OF PROCESS CONTROL
no. 140,
ISSN: 0959-1524 - Language:
- English
- Publication year:
- 2024
- Bibliographic description:
- Ujazdowski T., Piotrowski R., Banach M.: A stochastic approach for the solution of single and multi – objective optimisation problems of biological processes in sequencing batch reactor// JOURNAL OF PROCESS CONTROL -Vol. 140 (2024),iss. 103266 (2024),
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.jprocont.2024.103266
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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