Average modeling and evaluation of 18-pulse autotransformer rectifier unit without interphase transformers
Author(s) -
Shahbaz Khan,
Xiaobin Zhang,
Husan Ali,
Haider Zaman,
Muhammad Saad,
Bakht Muhammad Khan
Publication year - 2018
Publication title -
turkish journal of electrical engineering and computer sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 30
eISSN - 1303-6203
pISSN - 1300-0632
DOI - 10.3906/elk-1611-35
Subject(s) - autotransformer , transformer , electrical impedance , control theory (sociology) , rectifier (neural networks) , electronic engineering , transfer function , computer science , engineering , electrical engineering , voltage , distribution transformer , artificial intelligence , machine learning , recurrent neural network , control (management) , stochastic neural network , artificial neural network
This paper presents an improved average model and evaluation of an 18-pulse autotransformer rectifier unit (ATRU) in differential delta configuration. Average models remove the switching behavior of diode rectifiers and high bandwidth transients, which not only facilitates simulation of power systems by reducing computational cost but also enables impedance-based stability analysis for large complex power systems. To experimentally validate the proposed average model, a 2-kW, 18-pulse ATRU has been tested and the results of the derived model are compared with those of the switching model and experimental prototype. Computed transfer function of load impedance from the proposed average model closely resembles those of the switching model and the experimentally measured results validate the modeling procedure. Furthermore, stability analysis of the 18-pulse ATRU may be executed based on the return ratio of source and load impedance.
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