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Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications

Author

Listed:
  • Miriam Benedetti

    (Energy, New Technology and Environment Agency (ENEA), Rome 00123, Italy)

  • Francesca Bonfà

    (Energy, New Technology and Environment Agency (ENEA), Rome 00123, Italy)

  • Vito Introna

    (Department of Enterprise Engineering, University of Rome Tor Vergata, Rome 00133, Italy)

  • Annalisa Santolamazza

    (Department of Enterprise Engineering, University of Rome Tor Vergata, Rome 00133, Italy)

  • Stefano Ubertini

    (DEIM School of Engineering, University of Tuscia, Viterbo 01100, Italy)

Abstract

Most manufacturing and process industries require compressed air to such an extent that in Europe, for instance, about 10% of the total electrical energy consumption of industries is due to compressed air systems (CAS). However, energy efficiency in compressed air production and handling is often ignored or underestimated, mainly because of the lack of awareness about its energy consumption, caused by the absence of proper measurements on CAS in most industrial plants. Therefore, any effective energy saving intervention on generation, distribution and transformation of compressed air requires proper energy information management. In this paper we demonstrate the importance of monitoring and controlling energy performance in compressed air generation and use, to enable energy saving practices, to enhance the outcomes of energy management projects, and to obtain additional benefits for non-energy-related activities, such as operations, maintenance management and energy accounting. In particular, we propose a novel methodology based on measured data, and baseline definition through statistical modelling and control charts. The proposed methodology is tested on a real compressed air system of a pharmaceutical manufacturing plant in order to verify its effectiveness and applicability.

Suggested Citation

  • Miriam Benedetti & Francesca Bonfà & Vito Introna & Annalisa Santolamazza & Stefano Ubertini, 2019. "Real Time Energy Performance Control for Industrial Compressed Air Systems: Methodology and Applications," Energies, MDPI, vol. 12(20), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3935-:d:277380
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    Cited by:

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    4. Doner, Nimeti & Ciddi, Kerem, 2022. "Regression analysis of the operational parameters and energy-saving potential of industrial compressed air systems," Energy, Elsevier, vol. 252(C).
    5. Fábio de Oliveira Neves & Henrique Ewbank & José Arnaldo Frutuoso Roveda & Andrea Trianni & Fernando Pinhabel Marafão & Sandra Regina Monteiro Masalskiene Roveda, 2022. "Economic and Production-Related Implications for Industrial Energy Efficiency: A Logistic Regression Analysis on Cross-Cutting Technologies," Energies, MDPI, vol. 15(4), pages 1-19, February.
    6. Annalisa Santolamazza & Daniele Dadi & Vito Introna, 2021. "A Data-Mining Approach for Wind Turbine Fault Detection Based on SCADA Data Analysis Using Artificial Neural Networks," Energies, MDPI, vol. 14(7), pages 1-25, March.
    7. Jaroslav Vrchota & Martin Pech & Ladislav Rolínek & Jiří Bednář, 2020. "Sustainability Outcomes of Green Processes in Relation to Industry 4.0 in Manufacturing: Systematic Review," Sustainability, MDPI, vol. 12(15), pages 1-47, July.
    8. Cabello Eras, Juan José & Sagastume Gutiérrez, Alexis & Sousa Santos, Vladimir & Cabello Ulloa, Mario Javier, 2020. "Energy management of compressed air systems. Assessing the production and use of compressed air in industry," Energy, Elsevier, vol. 213(C).

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