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Modeling and Control Strategies for Energy Management in a Wastewater Center: A Review on Aeration

Author

Listed:
  • Mukhammad Jamaludin

    (Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taichung City 402202, Taiwan)

  • Yao-Chuan Tsai

    (Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taichung City 402202, Taiwan)

  • Hao-Ting Lin

    (Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taichung City 402202, Taiwan)

  • Chi-Yung Huang

    (Department of Mechanical Engineering, National Chin-Yi University of Technology, Taichung City 41170, Taiwan)

  • Wonjung Choi

    (Department of Chemical Engineering, Changwon National University, Changwon 51140, Republic of Korea)

  • Jiang-Gu Chen

    (Taoyuan Northern District Reclaimed Center, Taoyuan 33071, Taiwan)

  • Wu-Yang Sean

    (Department of Bio-Industrial Mechatronics Engineering, National Chung Hsing University, Taichung City 402202, Taiwan)

Abstract

Effective modeling and management are critical in wastewater treatment facilities since the aeration process accounts for 65–70% of the overall energy consumption. This study assesses control strategies specifically designed for different sizes of WWTP, analyzing their economic, environmental, and energy-related effects. Small WWTPs see advantages from the utilization of on/off and proportional–integral–derivative (PID) control methods, resulting in 10–25% energy savings and the reduction in dissolved oxygen (DO) levels by 5–30%. Cascade control and model predictive control (MPC) improve energy efficiency by 15–30% and stabilize DO levels by 15–35% in medium-sized WWTPs. Advanced WWTPs that utilize technologies such as MPC integrated with artificial intelligence (AI) and machine learning (ML) can decrease energy usage by 30–40% and enhance DO levels by 35–40%. Life cycle assessment (LCA) demonstrates substantial decreases in greenhouse gas (GHG) emissions: 5–20% for small, 10–25% for medium, and 30–35% for large WWTPs. These findings illustrate the feasibility and expandability of these tactics in both controlled laboratory environments and real-world situations, emphasizing the significance of customized methods for improving energy efficiency and sustainability in wastewater treatment. Subsequent investigations should prioritize integrating renewable energy sources and resolving obstacles in developing nations to enhance wastewater treatment plants’ energy efficiency and sustainability.

Suggested Citation

  • Mukhammad Jamaludin & Yao-Chuan Tsai & Hao-Ting Lin & Chi-Yung Huang & Wonjung Choi & Jiang-Gu Chen & Wu-Yang Sean, 2024. "Modeling and Control Strategies for Energy Management in a Wastewater Center: A Review on Aeration," Energies, MDPI, vol. 17(13), pages 1-24, June.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3162-:d:1423561
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    References listed on IDEAS

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    1. Murray R. Hall & Anthony Priestley & Tim H. Muster, 2018. "Environmental Life Cycle Costing and Sustainability: Insights from Pollution Abatement and Resource Recovery in Wastewater Treatment," Journal of Industrial Ecology, Yale University, vol. 22(5), pages 1127-1138, October.
    2. Joana Cassidy & Tatiana Silva & Nuno Semião & Pedro Ramalho & Ana Rita Santos & João Faria Feliciano & Catarina Silva & Maria João Rosa, 2023. "Integrating Reliability and Energy Efficiency Assessments for Pinpointing Actionable Strategies for Enhanced Performance of Urban Wastewater Treatment Plants," Sustainability, MDPI, vol. 15(17), pages 1-13, August.
    3. John A. Jinapor & Shafic Suleman & Richard Stephens Cromwell, 2023. "Energy Consumption and Environmental Quality in Africa: Does Energy Efficiency Make Any Difference?," Sustainability, MDPI, vol. 15(3), pages 1-26, January.
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