Faculty Publications

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  • Item
    Integrated power flowand voltage regulation of stand-alone PV-fuel cell system with supercapacitors
    (Acta Press journals@actapress.com, 2017) Sabhahit, J.N.; Gaonkar, D.N.; Nempu, P.B.
    The output of the solar cell is fluctuating due to intermittency of solar irradiation. Hybridizing the solar photovoltaic (PV) system with other sources and appropriate storage devices is essential to generate electricity continuously. This paper presents the control strategies for a PV-fuel cell hybrid power system with supercapacitor bank for isolated load applications. Supercapacitor bank is controlled using a bidirectional DC/DC converter so as to regulate voltage at a DC link and to keep the system stable under transient load variations. The H-bridge inverter is controlled to regulate voltage and frequency across the load. The PV system is controlled to extract maximum power using the maximum power point tracking algorithm. This paper aims to provide a single-phase supply with constant voltage and frequency to the consumers with proper power sharing among different sources. The hybrid system is realized in Matlab/Simulink environment.
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    Voltage estimation of active distribution network using PMU technology
    (Institute of Electrical and Electronics Engineers Inc., 2021) Tangi, S.; Gaonkar, D.N.
    As the Distributed Generation (DG) is evolving, the distribution network has undergone tremendous change. The DG sources like wind and solar are intermittent in nature. Hence to estimate the Active distribution network's (ADN) parameters (Voltage and Current) accurately with the DG variation, the traditional offline method like long-term smart distribution network planning (with off-line variant) method is not feasible in terms of network's reliability and operation. In this work, an online voltage estimation technique using PMU (Phasor Measurement Unit) technology is proposed to enhance a distribution network's reliable operation and real-time monitoring. The proposed estimation method does not require PMU units at all nodes in the network. The estimation of unknown states information can be achieved from available PMU unit's data. The proposed methodology is economical and feasible for voltage estimation, and system observability as the number of PMU units required is less. The standard IEEE Distribution network systems are considered for checking the feasibility of the recommended technique. For the simulation of the case studies, MATLAB programming is used. A Forward and Backward sweep (FBS) load-flow algorithm is used to authenticate the proposed methodology. © 2013 IEEE.
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    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.
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    A Novel Approach for Steady State Calculations of VSC-HVDC Connected PMSG Based Offshore Wind Farms Integrated into Multi-Machine Systems
    (Taylor and Francis Ltd., 2023) Rashmi, n.; Gaonkar, D.N.
    Offshore wind farms equipped with Direct Drive Permanent Magnet Synchronous Generators (DD-PMSG) are drawing increased attention due to their advantage over other variable speed technologies. VSC-HVDC links are considered the most suitable option for transferring power to the onshore system. The integration of VSC-HVDC connected DD-PMSG based offshore wind farms into multi-machine systems is explored in this paper. A novel approach for power flow and initial condition calculations is proposed to facilitate dynamic analysis of the system. For three cases of the most commonly specified quantities of the wind farm, efficient methods have been described. The cases comprise combinations of data like the total output of the wind farm, the number of wind turbines, the wind speed, or the output of individual wind turbine, which are frequently given in literature. This approach enables the user to build the dynamic model of the system in any basic graphical dynamic modeler and numerical computational software without requiring power system toolboxes or electromagnetic transient packages. The proposed methods are highly effective for studies focusing primarily on the dynamic aspects and controls of the system. Case studies and simulations are conducted to verify the proposed technique. © 2023 Taylor & Francis Group, LLC.
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    Probabilistic Optimal Active and Reactive Power Dispatch including Load and Wind Uncertainties considering Correlation
    (Hindawi Limited, 2023) Mahmmadsufiyan, M.; Gaonkar, D.N.; Nuvvula, R.S.S.; P Kumar, P.P.; Khan, B.
    The increased integration of renewable energies (REs) raised the uncertainties of power systems and has changed the approach to dealing with power system challenges. Hence, the uncertain nature of all the power system variables needs to be considered while dealing with the optimal planning and operation of modern power systems. This paper presents a probabilistic optimal active and reactive power dispatch (POARPD) based on the point estimate method (PEM), considering the uncertainties associated with load variation and wind power generation. In the POARPD, the deterministic optimal active and reactive power dispatch (OARPD) is performed in two stages, which gives a deterministic two-stage OARPD (TSOARPD). The objectives of TSOARPD are the operating cost (OC) minimization in stage 1 and voltage stability (VS) maximization in stage 2, whereas the VS is improved by maximizing the system's reactive power reserve (RPR). In this paper, instead of using multiobjective optimal power flow, this TSOARPD is used to give more importance to VS when the system is substantially loaded. The POARPD problem is solved using PEM for modified IEEE-9 bus and standard IEEE-30 bus test systems by considering the correlation between the loads. The results are compared with Monte Carlo simulation (MCS). While solving POARPD, the voltage-dependent load model is used to account for the real-time voltage dependency of power system loads. This paper discusses the detailed procedure of solving POARPD by considering correlation and the increased nonlinearities by giving more importance to VS when the system is heavily loaded. © 2023 Mahmmadsufiyan Shaik et al.
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    Nataf-KernelDensity-Spline-based point estimate method for handling wind power correlation in probabilistic load flow
    (Elsevier Ltd, 2024) Mahmmadsufiyan, M.; Gaonkar, D.N.; Nuvvula, R.S.S.; Muyeen, S.M.; Shezan, S.A.; Shafiullah, G.M.
    Modern power systems integrated with renewable energies (REs) contain many uncertainties. The proposed method introduces a novel approach to address the challenges associated with wind power generation uncertainty in probabilistic load flow (PLF) studies. Unlike conventional methods that use wind speed as an input, the paper advocates for utilizing wind generator output power (WGOP) as an input to the point estimate method (PEM) in solving PLF. The uniqueness lies in recognizing the distinct behavior of wind power uncertainty, where not all random samples of wind speed contribute to actual wind power production. The paper suggests a Nataf-KernelDensity-Spline-based PEM, combining the Nataf transformation, Kernel density estimation (KDE), and cubic spline interpolation. This innovative integration effectively manages wind power correlation within the analytical framework. By incorporating spline interpolation and kernel density estimation into the traditional PEM, the proposed method significantly enhances accuracy. To validate the effectiveness of the proposed approach, the method is applied to IEEE-9 and IEEE-57 bus test systems, considering uncertainties related to load, wind power generation (WPG), solar power generation (SPG), and conventional generator (CoG) outages. Comparative analysis with Monte Carlo simulation (MCS) results demonstrates that the proposed method outperforms the conventional PEM in terms of accuracy. Overall, the paper contributes a pioneering solution that not only highlights the importance of using WGOP as an input in PLF but also introduces a sophisticated method that surpasses traditional approaches, improving accuracy in power system studies involving renewable energy integration. The accuracy of the proposed method is validated by comparing its results with those obtained through Monte Carlo simulation (MCS), where the proposed method yields more accurate results than the conventional PEM. © 2023 Elsevier Ltd