Faculty Publications
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Item Model predictive controlled three-level bidirectional converter with voltage balancing capability for setting up EV fast charging stations in bipolar DC microgrid(Springer Science and Business Media Deutschland GmbH, 2022) Nisha, K.S.; Gaonkar, D.N.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.Item Operation and control of multiple electric vehicle load profiles in bipolar microgrid with photovoltaic and battery energy systems(Elsevier Ltd, 2023) Nisha, K.S.; Gaonkar, D.N.; Sabhahit, N.S.Charging of electric vehicles is going to be a major electrical load in the near future, as more and more population shift to electric auto-motives from conventional internal combusted engine-powered vehicles. Integration of electric vehicle charging stations (EVCS) might even burden the existing grid to a point of collapse or grid failure. Establishing charging stations interfaced with bipolar DC microgrids along the roads and highways is the most realistic and feasible solution to avoid the overburdening of the existing power system. The bipolar DC microgrid is a far better microgrid structure than the unipolar microgrid structure in many aspects like reliability, flexibility, and controllability. It can provide multiple voltage level interfaces according to the load demands, which is very apt for different charging levels of electric vehicles (EVs). Operation of multiple sources and multiple loads connected to bipolar DC microgrid will affect DC voltage regulation, capacitance-voltage balancing, and overall stable operation of the grid. In order to mitigate these power quality problems arising in multi-node bipolar DC microgrids, a decentralized model predictive control is proposed in this paper. EV charging load profiles are modeled and developed by considering standard driving cycles, state of charge, and power demand of multiple vehicles to study the effect of unpredictable varying EV loads in the bipolar DC microgrid. EVCS thus modeled are connected to solar photovoltaic-battery energy storage fed bipolar DC microgrid with three-level/bipolar converters and analyzed under dynamic conditions for capacitance–voltage unbalance mitigation, voltage regulation, and the stability of operation with model predictive control. Simulation studies are carried out in MATLAB/Simulink to verify the effectiveness of the system. © 2022 Elsevier Ltd