Modelling of variable‐speed refrigeration for fast‐frequency control in low‐inertia systems. Issue 6 (19th December 2020)

• Record Type: Journal Article
• Authors: Vorwerk, Johanna; Markovic, Uros; Aristidou, Petros; Vrettos, Evangelos; Hug, Gabriela
• Is Part Of: IET smart grid. Volume 3:Issue 6(2020)
• Page Start: 924
• Page End: 936
• Publication Date: 2020-12-19
• Subjects: time‐domain analysis -- transfer functions -- power system control -- frequency control -- brushless DC motors -- power grids -- reduced order systems -- frequency response -- frequency‐domain analysis -- refrigeration -- power system stability; fast‐frequency control -- low‐inertia systems -- power systems -- shiftable loads -- thermal loads -- thermal storage time constants -- variable‐speed refrigeration technology -- brushless DC motors -- fast‐frequency response -- single‐phase VSR unit -- small‐signal stability analysis -- large‐scale systems -- reduced‐order models -- time‐domain simulations -- frequency‐domain analyses; Smart power grids -- Periodicals; Computer science -- Periodicals; Energy industries -- Periodicals; Broadcasting -- Periodicals; 333.79110285
• DOI: 10.1049/iet-stg.2020.0154
• Languages: English
• ISSNs: 2515-2947

Abstract

Abstract : 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.