
Modelling, simulating and parameter designing for traction power system with bidirectional converter devices
Author(s) -
Zhang Jian,
Liu Wei,
Tian Zhongbei,
Zhang Hao,
Zeng Jiaxin,
Qi He
Publication year - 2022
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/gtd2.12281
Subject(s) - converters , voltage , rectifier (neural networks) , constraint (computer aided design) , control theory (sociology) , power (physics) , traction power network , train , traction (geology) , computer science , electric power system , engineering , electrical engineering , control (management) , physics , artificial neural network , mechanical engineering , stochastic neural network , cartography , quantum mechanics , machine learning , artificial intelligence , recurrent neural network , geography
The bidirectional converter device (BCD) can substitute the substation rectifier and the energy feedback system (EFS) by transforming energy between the AC side and DC side. However, the performance of the railway system with BCDs as only converters has not been fully understood. A simulation approach is required to evaluate the system performance and guide the design. In this paper, the traction power supply system considering the capacity constraint of BCDs is modelled first, and the AC/DC power calculating algorithm is studied. A three‐layer double‐loop parameter designing strategy based on the enhanced brute force is proposed, which considers the N −1 principle. In the case study, the power source model for trains and power constraint for BCDs are verified. The boundary configuration set is obtained. The capacity of BCDs is at least 7 MW, while the slope is 0 and the no‐load voltage is between 1730 and 1750 V. Finally, compared with the system with rectifiers and EFSs, the system with BCDs has better performance, which is 46.7 V less of the rail potential, 127.8 V less of network voltage fluctuation, and 735.56 kWh per hour more of the feedback energy.