Modelling of variable‐speed refrigeration for fast‐frequency control in low‐inertia systems

In modern power systems, shiftable loads contribute to the flexibility needed to increase robustness and ensure security. Thermal loads are among the most promising candidates for providing such service due to the large thermal storage time constants. This study demonstrates the use of variable‐spee...

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Bibliographic Details
Published in:IET smart grid 2020-12, Vol.3 (6), p.924-936
Main Authors: Vorwerk, Johanna, Markovic, Uros, Aristidou, Petros, Vrettos, Evangelos, Hug, Gabriela
Format: Article
Language:English
Subjects:
brushless DC motors
Brushless motors
Computing costs
Cost analysis
D C motors
Dynamic models
Eigenvalues
Electric motors
Electricity distribution
Energy consumption
fast-frequency control
fast-frequency response
Frequency control
Frequency response
frequency-domain analyses
frequency-domain analysis
Heat
Inertia
large-scale systems
low-inertia systems
power grids
power system control
power system stability
power systems
reduced order systems
reduced-order models
Refrigeration
Robust control
shiftable loads
Simulation
single-phase vsr unit
small-signal stability analysis
Stability analysis
Systems analysis
Systems stability
Temperature
Thermal analysis
thermal loads
Thermal storage
thermal storage time constants
time-domain analysis
time-domain simulations
Transfer functions
variable-speed refrigeration technology
Variables
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Summary:In modern power systems, shiftable loads contribute to the flexibility needed to increase robustness and ensure security. Thermal loads are among the most promising candidates for providing such service due to the large thermal storage time constants. This study demonstrates the use of variable‐speed refrigeration (VSR) technology, based on brushless DC motors, for the fast‐frequency response. First, the authors derive a detailed dynamic model of a single‐phase VSR unit suitable for time‐domain and small‐signal stability analysis in low‐inertia systems. For analysing dynamic interactions with the grid, they consider the aggregated response of multiple devices. However, the high computational cost involved in analysing large‐scale systems leads to the need for reduced‐order models. Thus, a set of reduced‐order models is derived through transfer function fitting of data obtained from time‐domain simulations of the detailed model. The modelling requirements and the accuracy versus computational complexity trade‐off are discussed. Finally, the time‐domain performance and frequency‐domain analyses reveal substantial equivalence between the full‐ and suitable reduced‐order models, allowing the application of simplified models in large‐scale system studies.
ISSN:2515-2947
2515-2947
DOI:10.1049/iet-stg.2020.0154