Open AccessModular soft‐switching converter in DC micro‐grid system applications
Author(s) -
Lin B.R.
Publication year - 2018
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2018.0564
Subject(s) - electrical engineering , rectifier (neural networks) , photovoltaic system , converters , capacitor , energy storage , voltage , renewable energy , engineering , power electronics , electronic engineering , power (physics) , computer science , physics , stochastic neural network , quantum mechanics , machine learning , recurrent neural network , artificial neural network
Owing to environmental issue and global temperature rise, the growth of renewable energy sources such as photovoltaic arrays, fuel cells and wind turbine power has been developed. Therefore, the direct current (DC) micro‐grid distributed systems are more and more important to integrate renewable energy sources, energy storage devices, local DC loads or alternative current (AC) loads and AC micro‐grid through AC–DC converters to achieve high reliability and efficiency in power systems. For industry and transportation applications such as metro and light transit, the preferred voltage level on DC micro‐grid system is recommended as 600–900 V. The proposed DC–DC converter contains three half‐bridge circuits with a series–parallel connection at primary–secondary sides so as to decrease voltage rating of active devices and current rating of rectifier diodes. Asymmetric pulse‐width modulation scheme is used to realise the soft‐switching turn‐on for active devices and the switching losses of power devices can be further reduced. To overcome input split voltage balance issue, flying capacitors are employed between two cascaded half‐bridge circuits and the voltage rating of each active device is limited at V in /3. Finally, experiments with a laboratory prototype are provided to verify the theoretical analysis and circuit performance.