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Continuously-stirred Anaerobic Digester to Convert Organic Wastes into Biogas: System Setup and Basic Operation
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Boosting biogas production through innovative data-driven modeling and optimization methods at NJWTP.

Jingsong Duan1,2,3, Guohua Cao4,5, Guoqing Ma1,3,6,7

  • 1School of Mechanical and Electrical Engineering, Changchun University of Science and Technology, Changchun, 130022, Jilin, China.

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|February 9, 2025
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A novel Deep Belief Network with Boosted Osprey Optimization Algorithm (DBN-BOOA) significantly enhances biogas production from wastewater. This data-driven approach optimizes operational parameters for increased energy recovery and reduced sludge.

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Area of Science:

  • Environmental Engineering
  • Biotechnology
  • Data Science

Background:

  • Wastewater treatment plants (WWTPs) generate significant sludge, presenting disposal challenges and opportunities for energy recovery.
  • Anaerobic digestion is a key process for converting organic waste into biogas, a renewable energy source.
  • Optimizing anaerobic digestion requires sophisticated modeling to manage complex biological and operational variables.

Purpose of the Study:

  • To develop and evaluate data-driven models for enhancing biogas production via anaerobic digestion of wastewater sludge.
  • To compare the performance of Deep Belief Network (DBN), DBN with Osprey Optimization Algorithm (DBN-OOA), and DBN with Boosted Osprey Optimization Algorithm (DBN-BOOA).
  • To identify optimal operational parameters for maximizing biogas yield and minimizing sludge production.

Main Methods:

  • Collected 180 data points from Nanjing Jiangnan Wastewater Treatment Plant (NJWTP) between 2016 and 2018.
  • Developed and compared three machine learning models: DBN, DBN-OOA, and DBN-BOOA.
  • Utilized statistical metrics including correlation coefficient (R), root mean square error (RMSE), and index of agreement (IA) for model evaluation.

Main Results:

  • The DBN-BOOA model achieved superior performance with R=0.98, RMSE=0.41 m³/min, and IA=0.99.
  • DBN-BOOA significantly outperformed standalone DBN and DBN-OOA models in accuracy and optimization.
  • Identified optimal parameters leading to a maximum biogas production of 31.35 m³/min.

Conclusions:

  • The DBN-BOOA model offers a highly accurate and efficient method for optimizing anaerobic digestion and biogas production.
  • This data-driven approach requires no input variable pre-processing, making it practical for real-world applications.
  • The DBN-BOOA model provides a user-friendly solution for wastewater treatment plant operators to enhance biogas yields and manage sludge effectively.