Data-driven analysis and prediction of wastewater treatment plant performance: Insights and forecasting for sustainable operations.

Journal: Bioresource technology
Published Date: Oct 28, 2023

Abstract

This study presents a comprehensive performance and forecasting analysis of the As-Samra wastewater treatment plant (WWTP) in Jordan, with two main objectives. Firstly, a thorough evaluation of the plant's performance is conducted. The analysis involves independently assessing historical operational conditions, plant production, and their statistical correlations using various statistical techniques. The second objective focuses on developing a data-driven forecasting approach to predict the plant's production one month in advance, using multiple machine learning models. The results highlight the effectiveness of principal component analysis (PCA) in simplifying operational data, revealing distinct operational clusters, and identifying seasonal production patterns while showing correlations between operational conditions and overall power production. The support vector machine (SVM) forecasting model emerged as the top performer, showcasing the potential of a hybrid forecasting approach. The findings offer valuable perspectives for enhancing operational efficiency, refining production planning, and ultimately improving the environmental impact of the plant.

Authors

  • Sameer Al-Dahidi
    Department of Mechanical and Maintenance Engineering, School of Applied Technical Sciences, German Jordanian University, Amman 11180, Jordan. Electronic address: sameer.aldahidi@gju.edu.jo.
  • Mohammad Alrbai
    Department of Mechanical Engineering, School of Engineering, University of Jordan, Amman 11942, Jordan. Electronic address: m.alrbai@ju.edu.jo.
  • Loiy Al-Ghussain
    Energy Systems and Infrastructure Analysis Division, Argonne National Laboratory, Lemont, IL 60439, USA. Electronic address: lalghussain@anl.gov.
  • Ali Alahmer
    Department of Mechanical Engineering, Tuskegee University, Tuskegee, AL 36088, USA; Department of Mechanical Engineering, Faculty of Engineering, Tafila Technical University, Tafila 66110, Jordan. Electronic address: a.alahmer@ttu.edu.jo.
  • Hassan S Hayajneh
    Department of Engineering Technology, College of Technology, Purdue University Northwest, 2200, USA. Electronic address: hayajneh@pnw.edu.

Keywords

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