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Impact of Demand Side Response on a Commercial Retail Refrigeration System

Author

Listed:
  • Ibrahim M. Saleh

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK
    These authors contributed equally to this work.)

  • Andrey Postnikov

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK
    These authors contributed equally to this work.)

  • Corneliu Arsene

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK)

  • Argyrios C. Zolotas

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK)

  • Chris Bingham

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK)

  • Ronald Bickerton

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK)

  • Simon Pearson

    (School of Engineering, University of Lincoln, Brayford Pool, Lincoln LN6 7TS, UK)

Abstract

The UK National Grid has placed increased emphasis on the development of Demand Side Response (DSR) tariff mechanisms to manage load at peak times. Refrigeration systems, along with HVAC, are estimated to consume 14% of the UK’s electricity and could have a significant role for DSR application. However, characterized by relatively low individual electrical loads and massive asset numbers, multiple low power refrigerators need aggregation for inclusion in these tariffs. In this paper, the impact of the Demand Side Response (DSR) control mechanisms on food retailing refrigeration systems is investigated. The experiments are conducted in a test-rig built to resemble a typical small supermarket store. The paper demonstrates how the temperature and pressure profiles of the system, the active power and the drawn current of the compressors are affected following a rapid shut down and subsequent return to normal operation as a response to a DSR event. Moreover, risks and challenges associated with primary and secondary Firm Frequency Response (FFR) mechanisms, where the load is rapidly shed at high speed in response to changes in grid frequency, is considered. For instance, measurements are included that show a significant increase in peak inrush currents of approx. 30% when the system returns to normal operation at the end of a DSR event. Consideration of how high inrush currents after a DSR event can produce voltage fluctuations of the supply and we assess risks to the local power supply system.

Suggested Citation

  • Ibrahim M. Saleh & Andrey Postnikov & Corneliu Arsene & Argyrios C. Zolotas & Chris Bingham & Ronald Bickerton & Simon Pearson, 2018. "Impact of Demand Side Response on a Commercial Retail Refrigeration System," Energies, MDPI, vol. 11(2), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:371-:d:130271
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    References listed on IDEAS

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    1. Qadrdan, Meysam & Cheng, Meng & Wu, Jianzhong & Jenkins, Nick, 2017. "Benefits of demand-side response in combined gas and electricity networks," Applied Energy, Elsevier, vol. 192(C), pages 360-369.
    2. Alexander Kies & Bruno U. Schyska & Lueder Von Bremen, 2016. "The Demand Side Management Potential to Balance a Highly Renewable European Power System," Energies, MDPI, vol. 9(11), pages 1-14, November.
    3. Kremers, Enrique & González de Durana, José Marı´a & Barambones, Oscar, 2013. "Emergent synchronisation properties of a refrigerator demand side management system," Applied Energy, Elsevier, vol. 101(C), pages 709-717.
    4. Cheng, Meng & Wu, Jianzhong & Galsworthy, Stephen J. & Gargov, Nikola & Hung, William H. & Zhou, Yue, 2017. "Performance of industrial melting pots in the provision of dynamic frequency response in the Great Britain power system," Applied Energy, Elsevier, vol. 201(C), pages 245-256.
    5. Grünewald, Philipp & Torriti, Jacopo, 2013. "Demand response from the non-domestic sector: Early UK experiences and future opportunities," Energy Policy, Elsevier, vol. 61(C), pages 423-429.
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    Cited by:

    1. Postnikov, A. & Albayati, I.M. & Pearson, S. & Bingham, C. & Bickerton, R. & Zolotas, A., 2019. "Facilitating static firm frequency response with aggregated networks of commercial food refrigeration systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Mohammad Reza Zavvar Sabegh & Chris Bingham, 2019. "Model Predictive Control with Binary Quadratic Programming for the Scheduled Operation of Domestic Refrigerators," Energies, MDPI, vol. 12(24), pages 1-20, December.

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