Model predictive controlled three-level bidirectional converter with voltage balancing capability for setting up EV fast charging stations in bipolar DC microgrid

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Date

2022

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Springer Science and Business Media Deutschland GmbH

Abstract

Transportation electrification and charging infrastructure development has to gain momentum in order to go hand-in-hand with the fast advances in the electric vehicle technology. Setting up dc fast charging stations connected to bipolar DC microgrid is a great viable option to utilize the distributed energy resources for transportation electrification. It also helps to eliminate power quality issues in ac grid that may arise due to the unpredictable charging/discharging behaviour of EVs. This paper focuses on model predictive control of a three-level bidirectional dc–dc converter suitable for interconnecting bipolar DC microgrid with dc fast charging stations or battery energy storage. State space analysis is done, and discrete model is developed. Simulation of the proposed system with model predictive control is done in Simulink MATLAB. Real-time hardware in loop performance is tested and verified using Typhoon HIL 402. The proposed converter is able to mitigate the voltage unbalance issues arising in the bipolar DC microgrid and is capable of controlling bidirectional power flow, hence suitable for V2G/G2Voperation. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Keywords

Capacitance, Charging (batteries), Electric load flow, Electric utilities, Energy resources, Microgrids, Model predictive control, Bidirectional three-level converter, Bipolar dc microgrid, Capacitance voltage, Capacitance voltage unbalance, Charging station, Dc micro-grid, Discrete state space, Discrete state space modeling, EV Charging, EV charging station, Hardware in loop, Model-predictive control, State-space models, Three-level converters, Voltage unbalances, MATLAB

Citation

Electrical Engineering, 2022, 104, 4, pp. 2653-2665

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