Facilitating static firm frequency response with aggregated networks of commercial food refrigeration systems

A. Postnikov, I.M. Albayati, S. Pearson, C. Bingham, R. Bickerton and A. Zolotas

Applied Energy, 2019, vol. 251, issue C, -

Abstract: Aggregated electrical loads from massive numbers of distributed retail refrigeration systems could have a significant role in frequency balancing services. To date, no study has realised effective engineering applications of static firm frequency response to these aggregated networks. Here, the authors present a novel and validated approach that enables large scale control of distributed retail refrigeration assets. The authors show a validated model that simulates the operation of retail refrigerators comprising centralised compressor packs feeding multiple in-store display cases. The model was used to determine an optimal control strategy that both minimised the engineering risk to the pack during shut down and potential impacts to food safety. The authors show that following a load shedding frequency response trigger the pack should be allowed to maintain operation but with increased suction pressure set-point. This reduces compressor load whilst enabling a continuous flow of refrigerant to food cases. In addition, the authors simulated an aggregated response of up to three hundred compressor packs (over 2 MW capacity), with refrigeration cases on hysteresis and modulation control. Hysteresis control, compared to modulation, led to undesired load oscillations when the system recovers after a frequency balancing event. Transient responses of the system during the event showed significant fluctuations of active power when compressor network responds to both primary and secondary parts of a frequency balancing event. Enabling frequency response within this system is demonstrated by linking the aggregated refrigeration loads with a simplified power grid model that simulates a power loss incident.

Keywords: Thermostatically controlled loads; Firm frequency response; Demand side management; Refrigeration systems; Computer simulation; Modelling (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1016/j.apenergy.2019.113357

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