Faculty Publications
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Item Enhancing Voltage Stability in Bipolar Microgrids(Institute of Electrical and Electronics Engineers Inc., 2024) Patil, V.S.; Gaonkar, D.N.This work proposes a solution for effectively integrating renewable energy systems into EV charging stations, focusing specifically on a bipolar DC microgrid framework to address increased loads. One of the main challenges tackled is asymmetrical loading within the bipolar DC network, which can lead to voltage drops at the neutral point. To address this, the paper examines a DC-to-DC converter with an integrated output voltage balancing method, eliminating the need for additional converters or control mechanisms. It also examines the design of a compensator for the closed-loop control of the DC-to-DC converter by developing a state-space model of the examined topology, obtaining a small-signal transfer function, and employing a k-factor method to design a compensator for voltage control. The proposed techniques and designs are validated through mathematical modeling and simulations using MATLAB/Simulink, supported by Typhoon HIL experimentation. The findings show significant potential for improving power transfer efficiency in practical EV charging station applications. © 2024 IEEE.Item A comprehensive review on control techniques for power management of isolated DC microgrid system operation(Institute of Electrical and Electronics Engineers Inc., 2021) Bhargavi, K.M.; Sabhahit, N.S.; Gaonkar, D.N.; Shrivastava, A.; Jadoun, V.K.The present research investigations in power management fraternity are focused towards the realization of smart microgrid (MG) technologies. Due to intrinsic advantages of Direct Current (DC) system in terms of compatibility with power generation sources, modern loads and storage devices, DC MG has becoming popular over Alternate Current (AC) system. A secondary voltage and current control schemes of DC MG system are mainly based on the distributed consensus control of Multi-agent system (MAS) to balance generation and the demand. The basic concern of the cooperative control of MAS is consensus, which is to design a suitable control law such that the output of all agents can achieve synchronization. The distributed consensus algorithm requires much less computational power and information exchange in between the neighbor's agent. Meanwhile the other controllers such as model predictive control (MPC) requires accurate dynamic models with high computational cost and it suffers from lack of flexibility. The hierarchical consensus control technique is classified into three levels according to their features, namely primary, secondary, and tertiary. MAS is a popular distributed platform to efficiently manage the secondary control level for synchronization and communication among the power converters in autonomous MGs. In this article, various primary control techniques for local voltage control, voltage restoration in the secondary control level and tertiary control for energy management techniques are discussed. With this, the key emphasis to reduce the voltage deviation and disturbances in a heterogeneous DC MG network solutions are discussed. Furthermore, to analyze the system response and the charging and discharging characteristics of the battery unit, the developed second order heterogeneous consensus controller is compared with the traditional homogeneous consensus control and droop control methods. Finally a detailed discussion on simulation case study using heterogeneous consensus control method over the traditional methods are provided using MATLAB/Simulink platform. © 2021 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.Item 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 Maximum span determination and optimal sizing of cable for improved performance of droop-controlled DC microgrid(Elsevier Ltd, 2024) Mathew, D.; Prabhakaran, P.DC microgrids are seen as smart solutions to interface DC loads and distributed energy resources (DERs). However, in DC microgrids, the placement of sources and loads as well as the size of cable impact the system's span, regulation of voltage, and losses. This paper proposes novel algorithms to determine the maximum span and optimal size of cable for the improved performance of a droop-controlled DC microgrid. The proposed algorithms utilize an improved power flow analysis (IPFA) method based on Newton-Raphson technique to determine the maximum span and the optimal size of cable, enhancing the voltage regulation and reducing the cost. Additionally, the impacts of power rating, droop constants, and size of cable on the DC microgrid's maximum span are investigated and reported. Owing to the intricate nature of the problem concerning the ideal size of cable for the droop-controlled DC microgrid, a heuristic optimization approach is employed. Further to enhance the rate of convergence and computational performance, an improved particle swarm optimization (IPSO) is also proposed. The constraint of keeping the bus voltage variations below the allowable voltage regulation limits is applied to the objective function of the optimization problem. In the case of a droop-controlled, DC microgrid having a specified configuration, the suggested algorithm can determine the ideal size of cable, guaranteeing both the least cost and enhanced voltage regulation. Comprehensive numerical and modelling results have been presented for a droop-controlled DC microgrid with different loads and DERs to verify the effectiveness of the proposed methods. Furthermore, the analysis reveals that configuration III of the DC microgrid with an optimal cable size of 19 mm2 lowers the absolute voltage regulation to as low as 1.06 V. The results of the detailed analysis validate the enhanced performance of the proposed algorithms and are highly useful to both system designers and consumers of the DC microgrids, eventually paving the way for the widespread use of DC microgrids in the future. © 2024 The Author(s)Item Optimal configuration for improved system performance of droop-controlled DC microgrid with distributed energy resources and storage(Elsevier Ltd, 2024) Mathew, D.; Prabhakaran, P.The placement of sources and loads in DC microgrids (DCMGs) influences the system's voltage regulation, span, and losses. In order to minimize losses and enhance voltage regulation, a unique algorithm for configuring a radial DCMG under droop control in an optimal way is presented in this paper. The suggested approach solves the optimal design problem by applying the power flow analysis technique. The genetic algorithm (GA), a heuristic method, is used to determine the ideal configuration because of the complexity of the optimization problem. An improved particle swarm optimization (IPSO)-based technique is also proposed for resolving the optimization issue to improve the convergence rate and computing efficiency. Appropriate modifications are proposed to yield an optimal configuration that results in the maximum achievable span for the radial, droop-controlled DCMG. To limit the bus voltage variations within the bounds, the objective functions of the optimization problem are appropriately formulated. In addition, the proposed algorithm is used to find the best position and power rating of a new distributed energy resource (DER) or load in the DCMG, in order to reduce system losses. A 5-bus, 500 W, radial, droop-controlled DCMG system's comprehensive numerical and simulation results are presented to validate the effectiveness of the proposed approaches. The findings are significant and useful for DCMG consumers as well as system designers. © 2024 Elsevier LtdItem Investigation and Performance Evaluation of Novel Single-Switch High-Gain DC-DC Converters for DC Microgrid Applications(Institute of Electrical and Electronics Engineers Inc., 2025) Diwakar Naik, M.; Vinatha Urundady, U.; Naik, M.; Bonthagorla, P.K.This paper introduces a novel single-switch, non-isolated high-gain DC-DC converter for solar photovoltaic (PV) and fuel-cell (FC) applications. These energy sources typically provide a continuous supply of current, necessitating a high-gain DC-DC converter that operates in continuous conduction mode (CCM). This converter draws a continuous input current from the supply and delivers a continuous output current to the load. The performance of the converter is thoroughly analyzed through the development of a state-space model and the derivation of the small signal transfer function, which helps in understanding the converter’s dynamic behavior. Detailed comparisons with existing converters are also presented. Furthermore, an output voltage controller is designed using the k-factor method to effectively regulate the output voltage without requiring a current sensor, even in the presence of input voltage variations. To validate the effectiveness of the converter and its controller, a 150 W prototype was constructed and experimentally verified in a laboratory setting. © 2013 IEEE.