TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Impedance-Based Stability Analysis of Paralleled Grid-Connected Rectifiers: Experimental Case Study in Data Center

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Artikkeli2109
Sivumäärä15
JulkaisuEnergies
Vuosikerta13
Numero8
DOI - pysyväislinkit
TilaJulkaistu - 2020
OKM-julkaisutyyppiA1 Alkuperäisartikkeli

Tiivistelmä

Grid-connected systems often consist of several feedback-controlled power-electronics converters that are connected in parallel. Consequently, a number of stability issues arise due to interactions among multiple converter subsystems. Recent studies have presented impedance-based methods to assess the stability of such large systems. However, only few real-life experiences have been previously presented, and practical implementations of impedance-based analysis are rare for large-scale systems that consist of multiple parallel-connected devices. This work presents a case study in which an unstable high-frequency operation, caused by multiple paralleled grid-connected rectifiers, of a 250 kW data center in southern Finland is reported and studied. In addition, the work presents an experimental approach for characterizing and assessing the system stability by using impedance measurements and an aggregated impedance-based analysis. Recently proposed wideband-identification techniques based on binary injection and Fourier methods are applied to obtain the experimental impedance measurements from the input terminals of a single data center rectifier unit. This work provides a practical approach to design and implement the impedance-based stability analysis for a system consisting of multiple paralleled grid-connected converters. It is shown that the applied methods effectively predict the overall system stability and the resonant modes of the system, even with very limited information on the system. The applied methods are versatile, and can be utilized in various grid-connected applications, for example, in adaptive control, system monitoring, and stability analysis.