Open AccessModelling method and applicability analysis of a reduced‐order inverter model for microgrid applications
Author(s) -
Yu Hongru,
Su Jianhui,
Wang Haining,
Wang Yiding,
Shi Yong
Publication year - 2020
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2020.0078
Subject(s) - microgrid , correctness , computer science , reduction (mathematics) , inverter , generality , stability (learning theory) , process (computing) , power (physics) , control theory (sociology) , control (management) , algorithm , mathematics , machine learning , artificial intelligence , psychology , physics , geometry , quantum mechanics , psychotherapist , operating system
A proper inverter model is an important tool for system stability analysis and parameter design. A complete model is accurate, but computationally expensive. While some reduced‐order models are available, they are inaccurate in certain situations, or lose generality as parameters change. The characteristics of these inverters are significantly different from those of synchronous machines with strong natural timescale separation. Although network dynamics and inner‐loop dynamics are relatively fast, they seem to have an impact on power loops with slow dynamics, and neglecting them can lead to questionable results. In this study, the limitations of existing general models are demonstrated, and their applicability is analysed. To address the reduced‐order precision problem, a process‐simplified reduction method and an efficient reduced‐order inverter model are proposed for microgrid applications. The developed model has higher precision and wider applicability while uncovering instability mechanisms and addressing other factors. Finally, the correctness of the theoretical analysis and the validity of the model reduction method are verified by comparative experiments.