Open AccessNon‐linear switched model for accurate voltage estimation and power flow analysis of DC railway systems
Author(s) -
Mayet Clément,
Arboleya Pablo,
Bouscayrol Alain,
Mohamed Bassam,
Delarue Philippe,
ElSayed Islam
Publication year - 2020
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/iet-est.2020.0048
Subject(s) - computation , traction (geology) , voltage drop , traction power network , voltage , traction substation , electric power system , control theory (sociology) , computer science , train , control engineering , power electronics , engineering , power (physics) , automotive engineering , electronic engineering , algorithm , electrical engineering , mechanical engineering , physics , control (management) , cartography , quantum mechanics , artificial intelligence , geography , transformer
Simulation tools are crucial to efficiently design the infrastructures and operations of DC electrical railway systems, including potential innovative technologies such as reversible traction power substations and energy storage systems. For this purpose, it is essential to accurately estimate the evolution of the voltage and power flows within the DC traction network, with fast computation time. This study, therefore, proposes a new simulation approach for fast and accurate voltage estimation and power flow analysis of DC railway systems. It is based on the use of non‐linear switched models for traction power substations and trains. The modified nodal analysis is extended to consider such models, including the voltage drop control of the different subsystems, avoiding the necessity to use complex numerical iterative solvers. This new approach is validated and compared to an existing dynamical model and a conventional static model. The comparisons prove the relevance of the new approach, which provides validated and accurate results (<2% error compared to the validated dynamical model) with fast computation time (speed up of 500 compared to the dynamical model). It can, therefore, be used to study, design, size, and optimise DC traction systems with new technologies aimed at saving braking energy.