Conference Papers
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Item Model predictive control of three level buck/boost converter for bipolar DC microgrid applications(Institute of Electrical and Electronics Engineers Inc., 2019) Nisha, K.S.; Gaonkar, D.N.Emergence of bipolar dc microgrids calls for the need of bipolar converter configurations for the integration of battery energy storage system (BESS), electric vehicle dc fast charging stations (EVCS) etc. This paper proposes model predictive control of a bipolar bidirectional buck/boost converter derived from three level converter (TLC) configuration in a bipolar dc microgrid. Bipolar dc microgrid is fed by power from solar PV systems and BESS. State space analysis is done and discrete model is developed. Simulation of the proposed system with model predictive control (MPC) is done in Simulink MATLAB and analysed for the voltage unbalance issues of bipolar dc microgrid under varying conditions of photovoltaic generations and load disturbance. From the simulation results, proposed converter with model predictive control technique gives faster response in mitigating the voltage unbalance and grid voltage regulation issues arising in bipolar dc microgrid. © 2019 IEEE.Item Predictive Control of Three Level Bidirectional Converter in Bipolar DC Microgrid for EV Charging Stations(Institute of Electrical and Electronics Engineers Inc., 2020) Nisha, K.S.; Gaonkar, D.N.This paper proposes model predictive control (MPC) of a bipolar bidirectional buck/boost converter derived from three level converter (TLC) configuration for integrating with electric vehicle charging station or battery energy storage system (BES) in bipolar dc microgrid structure. Bipolar dc microgrid considered here consists of two solar PV systems, dc loads and battery. The bidirectional power flow between grid and battery or EV charging stations is controlled considering the battery state of charge (SOC), total power generated and load demanded. Advantage of this converter is that it can address the dc grid voltage regulation and capacitance voltage balancing issues during variation of load and solar irradiation in bipolar dc microgrid. State space analysis is done and discrete model is developed. Simulation is done in Simulink MATLAB and analysed for voltage unbalance issues of bipolar dc microgrid under varying conditions of photovoltaic generations and load disturbance. Real time performance is tested and verified in hardware in loop environment using Typhoon HIL 402. © 2020 IEEE.Item Three-Level Boost Converter for EV Charging in Bipolar Microgrids(Institute of Electrical and Electronics Engineers Inc., 2024) Patil, V.S.; Nisha, K.S.; Gaonkar, D.N.The rapid expansion of microgrids, the surge in electric vehicle (EV) adoption, and the widespread use of renewable energy systems have created an urgent need for a state-of-the-art DC-DC converter with regulated DC bus voltage. To meet this demand and revolutionize power regulation in EV charging stations within bipolar microgrid environments, a three-level boost converter (3-L BC) has been devised. The three-level boost converter is a game-changing interface for bipolar DC microgrids and batteries, handling diverse power levels in positive and negative DC buses. The converter features a closed-loop control system and an incremental conductance-based Maximum Power Point Tracking (MPPT) technique to control power flow adeptly across the DC link poles. A proportional-integral (PI) controller is designed for each operating point using the k-factor approach. A small signal analysis determines the output voltage to the duty cycle transfer function. The PI controller generates a control signal for any operating point using the feedback signals and MPPT technique, thereby balancing the DC bus poles. An electric vehicle (EV) battery is linked to the DC bus for charging and discharging. The converter's performance is assessed using MATLAB/Simulink, and the results emphasize its crucial role in improving voltage stability, facilitating reliable EV charging infrastructure, and promoting sustainable energy practices. © 2024 IEEE.