{
  "abstract": "Wastewater treatment plants (WWTPs) are complex facilities that must be operated efficiently from both environmental and economic perspectives. They need to balance a range of often conflicting performance objectives, necessitating a plant-wide approach and multi-objective optimization. This paper presents an approach for dynamic plant-wide optimization of the effluent quality index ( E Q I ) and operational cost index ( O C I ) by employing reduced neuro-fuzzy models to represent performance indices, combined with simplified predictive control. The approach is validated through a one-year simulation using the plant-wide benchmark simulation model no. 2 (BSM2PSFe) and by dynamically optimizing the dissolved oxygen (DO) concentration set-point in an aerobic reactor. The Pareto front of optimal solutions is analyzed, and the individual indices are integrated into a single objective function by adjusting the weights of the criteria. The results show that the proposed optimization approach provides a better trade-off between the E Q I and O C I indices than constant DO set-point values. Compared to the DO set-point of 1.5 g/m 3 , the presented optimization case improves E Q I for 2.64% and O C I for 0.87%. The advantage of the approach, apart from plant-wide consideration, is its reliance on measurements available in practice, making it suitable for implementation in real WWTPs.",
  "abstract_shown": true,
  "affiliations": [
    "Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, Ljubljana, 1000, Slovenia; Corresponding author.",
    "Jožef Stefan Institute, Jamova cesta 39, Ljubljana, 1000, Slovenia",
    "Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, Ljubljana, 1000, Slovenia"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Gorazd Karer"
    },
    {
      "affs": [
        1
      ],
      "name": "Darko Vrečko"
    },
    {
      "affs": [
        1
      ],
      "name": "Nadja Hvala"
    },
    {
      "affs": [
        2
      ],
      "name": "Igor Škrjanc"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8k0n4pysrsbps.bib",
  "cited_by": 0,
  "doi": "10.1016/j.dwt.2026.102008",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S1944398626003826",
  "id": "8k0n4pysrsbps",
  "issns": [
    "1944-3986",
    "1944-3994"
  ],
  "landing_url": "https://doi.org/10.1016/j.dwt.2026.102008",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "QH540-549.5"
    ],
    [
      "lcc",
      "TD1-1066"
    ],
    [
      "openalex",
      "2310|Wastewater Treatment and Nitrogen Removal"
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  "openalex": "W7225174471",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/8k0n4pysrsbps.ris",
  "sources": [
    {
      "first_seen": "2026-11-09T14:21:32Z",
      "native_id": "00721798132b4837a0e19ec2274627ca",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.dwt.2026.102008"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "openalex:2310|Wastewater Treatment and Nitrogen Removal",
      "subfield": "environmental-science"
    }
  ],
  "title": "Dynamic plant-wide optimization of wastewater treatment plant performance using neuro-fuzzy models and predictive control",
  "title_text": "Dynamic plant-wide optimization of wastewater treatment plant performance using neuro-fuzzy models and predictive control",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T14:21:32Z",
  "url": "https://research.draconitic.com/paper/8k0n4pysrsbps",
  "venue": "Desalination and Water Treatment",
  "versions": []
}