Adaptive stochastic and hybrid nonlinear optimization algorithms for improving the effectiveness of the biological processes at WWTP
Wastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it i...
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| Vydáno v: | Biochemical engineering journal Ročník 193; s. 108852 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.04.2023
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| Témata: | |
| ISSN: | 1369-703X, 1873-295X |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Wastewater treatment plays an important factor in the modern world. Insufficient treatment may result in environmental pollution which can further lead to disasters and diseases. However, processes that take place inside wastewater treatment plants (WWTP) are highly complex in nature, therefore it is difficult to design an efficient, optimal control system. The problem regarding biochemical reactions inside Sequential Batch Reactor (SBR) is analyzed in this paper and the optimization problem is defined. Next, chosen optimization methods including both deterministic and metaheuristic algorithms are carefully described. Series of simulation experiments are conducted based on a verified model of SBR from Swarzewo Wastewater Treatment Plant (WWTP) - Northern Poland. The proposed optimal control system allowed to increase the efficiency, improve the quality of outflow (reduction of Chemical Oxygen Demand (COD), total nitrogen (Ntot) and total phosphorus (Ptot)) and reduce wastewater treatment costs.
•Dissolved oxygen control is very important for WWTP energy efficiency.•Hierarchical control system has been applied to the SBR and aeration system.•The optimal reference trajectory of the DO was calculated.•Simulation tests have been carried out. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1369-703X 1873-295X |
| DOI: | 10.1016/j.bej.2023.108852 |