1st International Conference on Industrial Networks and Intelligent Systems

Research Article

Performance Indicators for Complex Wastewater Pumping Stations and Pressure Main

Download920 downloads
  • @INPROCEEDINGS{10.4108/icst.iniscom.2015.258385,
        author={Kees Kooij and Sarah Muhle and Francois Clemens and Ivo Pothof and F.H. Blokzijl},
        title={Performance Indicators for Complex Wastewater Pumping Stations and Pressure Main},
        proceedings={1st International Conference on Industrial Networks and Intelligent Systems},
        publisher={ICST},
        proceedings_a={INISCOM},
        year={2015},
        month={4},
        keywords={wastewater performance indicator pumping online monitoring maintenance energy},
        doi={10.4108/icst.iniscom.2015.258385}
    }
    
  • Kees Kooij
    Sarah Muhle
    Francois Clemens
    Ivo Pothof
    F.H. Blokzijl
    Year: 2015
    Performance Indicators for Complex Wastewater Pumping Stations and Pressure Main
    INISCOM
    ICST
    DOI: 10.4108/icst.iniscom.2015.258385
Kees Kooij1,*, Sarah Muhle1, Francois Clemens2, Ivo Pothof2, F.H. Blokzijl3
  • 1: Deltares
  • 2: Delft University of Technology
  • 3: Municipality of Almere
*Contact email: kees.kooij@deltares.nl

Abstract

With increasing energy costs, concern on CO2 emission and growing interest in asset management, the online evaluation of pressurized wastewater systems provides an opportunity for optimizing performance. This paper describes a method that uses performance indicators (PIs) derived from monitoring data and model simulation results using an online system. Malfunctioning, or underperformance can be detected in an early stage, which enables to take measures in terms of replacement or reparation based on the actual status of the system rather than rely on the effectiveness of regular, scheduled, inspection. The city of Almere’s wastewater transport system is used as a case study and demonstrates the introduction, application and interpretation of these PIs as well as the obtainable reduction in energy consumption using on-line data on the systems behaviour.