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 LtdItem Optimal Placement and Sizing of Electric Vehicle Charging Infrastructure in a Grid-Tied DC Microgrid Using Modified TLBO Method(MDPI, 2023) Krishnamurthy, N.K.; Sabhahit, J.N.; Jadoun, V.K.; Gaonkar, D.N.; Shrivastava, A.; Rao, V.S.; Kudva, G.In this work, a DC microgrid consists of a solar photovoltaic, wind power system and fuel cells as sources interlinked with the utility grid. The appropriate sizing and positioning of electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) are concurrently determined to curtail the negative impact of their placement on the distribution network’s operational parameters. The charging station location problem is presented in a multi-objective context comprising voltage stability, reliability, the power loss (VRP) index and cost as objective functions. RES and EVCS location and capacity are chosen as the objective variables. The objective functions are tested on modified IEEE 33 and 123-bus radial distribution systems. The minimum value of cost obtained is USD 2.0250 × 106 for the proposed case. The minimum value of the VRP index is obtained by innovative scheme 6, i.e., 9.6985 and 17.34 on 33-bus and 123-bus test systems, respectively. The EVCSs on medium- and large-scale networks are optimally placed at bus numbers 2, 19, 20; 16, 43, and 107. There is a substantial rise in the voltage profile and a decline in the VRP index with RESs’ optimal placement at bus numbers 2, 18, 30; 60, 72, and 102. The location and size of an EVCS and RESs are optimized by the modified teaching-learning-based optimization (TLBO) technique, and the results show the effectiveness of RESs in reducing the VRP index using the proposed algorithm. © 2023 by the authors.Item A Hybrid Islanding Detection Method Based on Lissajous Pattern Having Robust Performance Under Various Power Quality Scenarios(Institute of Electrical and Electronics Engineers Inc., 2023) Mondal, S.; Gayen, P.K.; Gaonkar, D.N.A fast, accurate, robust, and two-staged islanding detection technique (IDT) is proposed. It is the hybridization of second-order general integrator-frequency locked loop (SOGI-FLL), Lissajous pattern (LP), and active power absorption-cum-reactive power injection via dc-bus connected battery unit-based inverter. The LP is used to identify islanding condition on the basis of frequency variation of fundamental voltage. Here, the measured ac voltage signal is preprocessed by SOGI-FLL to obtain fundamental bus voltage under various power quality scenarios. This assures robust islanding detection by removing uncertainty, and thus, reliability is improved. The uncertainty effects due to the partial shading condition of the PV module (source-side disturbance) and weak grid-connected condition are avoided by dc-bus connected battery storage unit. Thus, it removes above-said limitations of the existing scheme. The LP-based detection within the nondetection zone is expedited due to active and reactive powers variation via controlling of the inverter and charging operation of the dc-bus connected battery unit. During the reactive power injection by solar inverter, active power is absorbed by dc-bus connected battery unit. In effect, an active power output of the inverter is reduced. Here, the reactive power injection at the reduced active power output condition of the inverter accelerates frequency variation allowing rapid islanding detection. The real-time experiments are carried out using Typhoon-HIL tools to compare the proposed method with other works reported in the literature. Improved performances under diversified scenarios are found in the proposed case. © 2007-2012 IEEE.