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Modeling of Electric Energy Consumption during Dairy Wastewater Treatment Plant Operation

Author

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  • Radosław Żyłka

    (Bielmlek Cooperative, 52 Wojska Polskiego St., 17-100 Bielsk Podlaski, Poland)

  • Wojciech Dąbrowski

    (Faculty of Civil Engineering and Environmental Science, Bialystok University of Technology, 45E Wiejska St., 15-351 Bialystok, Poland)

  • Paweł Malinowski

    (Department of Statistics and Medical Informatics, Medical University of Bialystok, 37 Szpitalna St., 15-295 Bialystok, Poland)

  • Beata Karolinczak

    (Faculty of Building Services, Hydro and Environmental Engineering, Warsaw University of Technology, 20 Nowowiejska St., 00-653 Warsaw, Poland)

Abstract

The intensification of biological wastewater treatment requires the high usage of electric energy, mainly for aeration processes. Publications on energy consumption have been mostly related to municipal wastewater treatment plants (WWTPs). The aim of the research was to elaborate on models for the estimation of energy consumption during dairy WWTP operation. These models can be used for the optimization of electric energy consumption. The research was conducted in a dairy WWTP, operating with dissolved air flotation (DAF) and an activated sludge system. Energy consumption was measured with the help of three-phase network parameter transducers and a supervisory control and data acquisition (SCADA) system. The obtained models provided accurate predictions of DAF, biological treatment, and the overall WWTP energy consumption using chemical oxygen demand (COD), sewage flow, and air temperature. Using the energy consumption of the biological treatment as an independent variable, as well as air temperature, it is possible to estimate the variability of the total electric energy consumption. During the summer period, an increase in the organic load (expressed as COD) discharged into the biological treatment causes higher electric energy consumption in the whole dairy WWTP. Hence, it is recommended to increase the efficiency of the removal of organic pollutants in the DAF process. An application for the estimation of energy consumption was created.

Suggested Citation

  • Radosław Żyłka & Wojciech Dąbrowski & Paweł Malinowski & Beata Karolinczak, 2020. "Modeling of Electric Energy Consumption during Dairy Wastewater Treatment Plant Operation," Energies, MDPI, vol. 13(15), pages 1-14, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3769-:d:388142
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    References listed on IDEAS

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    1. Longo, Stefano & d’Antoni, Benedetto Mirko & Bongards, Michael & Chaparro, Antonio & Cronrath, Andreas & Fatone, Francesco & Lema, Juan M. & Mauricio-Iglesias, Miguel & Soares, Ana & Hospido, Almudena, 2016. "Monitoring and diagnosis of energy consumption in wastewater treatment plants. A state of the art and proposals for improvement," Applied Energy, Elsevier, vol. 179(C), pages 1251-1268.
    2. Marcin Dębowski & Marcin Zieliński & Marta Kisielewska & Joanna Kazimierowicz, 2020. "Evaluation of Anaerobic Digestion of Dairy Wastewater in an Innovative Multi-Section Horizontal Flow Reactor," Energies, MDPI, vol. 13(9), pages 1-16, May.
    3. Venkatesh, G. & Brattebø, Helge, 2011. "Energy consumption, costs and environmental impacts for urban water cycle services: Case study of Oslo (Norway)," Energy, Elsevier, vol. 36(2), pages 792-800.
    4. Koenker, Roger & Park, Beum J., 1996. "An interior point algorithm for nonlinear quantile regression," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 265-283.
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    Cited by:

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    2. Chenxi Pang & Xi Luo & Bing Rong & Xuebiao Nie & Zhengyu Jin & Xue Xia, 2022. "Carbon Emission Accounting and the Carbon Neutralization Model for a Typical Wastewater Treatment Plant in China," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    3. Joanna Rodziewicz & Artur Mielcarek & Kamil Bryszewski & Wojciech Janczukowicz & Karolina Kłobukowska, 2022. "Energy Consumption for Nutrient Removal from High-Nitrate and High-Phosphorus Wastewater in Aerobic and Anaerobic Bioelectrochemical Reactors," Energies, MDPI, vol. 15(19), pages 1-15, October.
    4. Joanna Kazimierowicz & Izabela Bartkowska & Maria Walery, 2020. "Effect of Low-Temperature Conditioning of Excess Dairy Sewage Sludge with the Use of Solidified Carbon Dioxide on the Efficiency of Methane Fermentation," Energies, MDPI, vol. 14(1), pages 1-13, December.
    5. Katarzyna Ignatowicz & Jacek Piekarski & Paweł Kogut, 2021. "Influence of Selected Substrate Dosage on the Process of Biogas Installation Start-Up in Real Conditions," Energies, MDPI, vol. 14(18), pages 1-11, September.
    6. Katarzyna Ignatowicz & Gabriel Filipczak & Barbara Dybek & Grzegorz Wałowski, 2023. "Biogas Production Depending on the Substrate Used: A Review and Evaluation Study—European Examples," Energies, MDPI, vol. 16(2), pages 1-17, January.

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