Faculty Publications

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    Dynamic performance of microturbine generation system connected to a grid
    (2008) Gaonkar, D.N.; Pillai, G.N.; Patel, R.N.
    The interconnection of distribution generation systems into distribution networks has great impact on real-time system operation, control, and planning. It is widely accepted that microturbine generation (MTG) systems are currently attracting a lot of attention to meet customers' needs in the distributed power generation market. In order to investigate the performance of MTG systems, their efficient modeling is required. This article presents the dynamic model of an MTG system, suitable for grid connection to study the performance of the MTG system. The presented model uses back-to-back power electronic converter topology for grid connection, which allows the bidirectional power flow between the grid and MTG system. Thus, the need of separate starting arrangements during launching of the microturbine is avoided. The components of the system are built from the dynamics of each part with their interconnections. The dynamics of the model have been studied under various grid disturbance conditions. The converter control strategies for MTG system operation in grid-connected mode are presented in this article. This article also compares the various grid connection topologies suitable for MTG system interconnection. The simulation results show that the developed model performance is not affected by the grid disturbances considered in the study, and that it has the ability to adjust the supply as per the power requirements of the load within the MTG system rating.
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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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    Probabilistic Load Flow Approach Combining Cumulant Method and K-Means Clustering to Handle Large Fluctuations of Stochastic Variables
    (Institute of Electrical and Electronics Engineers Inc., 2023) Singh, V.; Moger, T.; Jena, D.
    The modern electrical power system faces various uncertainties, including load fluctuations, forced outages of conventional generators, network branches. Furthermore, the rising penetration of wind power generation introduces additional uncertainty, causing difficulties in power system planning, operation. This paper uses an analytical probabilistic load flow approach to account for all such uncertainties. The random branch outages are simulated using the fictional powers injections into the relevant nodes. A fuzzy method is used to perform contingency sequencing to avoid masking mistakes that might occur when utilizing performance index-based sequencing methods. The sparse Jacobian inverse is eliminated to preserve storage space, accelerate the computation. A modified Cumulant method is used in conjunction with the K-means clustering process to deal with the substantial fluctuations of the input variables. In the proposed approach, the correlated samples are generated using inverse Nataf transformation. These correlated samples are clustered using K-means clustering. The Cumulant method is applied within each cluster, total probability law is used to integrate each cluster's findings. The proposed PLF is tested on 24-bus, 259-bus wind integrated equivalent systems. Compared with the Monte-Carlo simulation, the proposed PLF yields computationally efficient, more accurate findings. © 1972-2012 IEEE.
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    Exploring the Potential of Kite-Based Wind Power Generation: An Emulation-Based Approach
    (Multidisciplinary Digital Publishing Institute (MDPI), 2023) Castelino, R.V.; Kumar, P.; Kashyap, Y.; Karthikeyan, A.; Sharma K, M.; Karmakar, D.; Kosmopoulos, P.
    A Kite-based Airborne Wind Energy Conversion System (KAWECS) works by harnessing the kinetic energy from the wind and converting it into electric power. The study of the dynamics of KAWECS is fundamental in researching and developing a commercial-scale KAWECS. Testing an actual KAWECS in a location with suitable wind conditions is only sometimes a trusted method for conducting research. A KAWECS emulator was developed based on a Permanent Magnet Synchronous Machine (PMSM) drive coupled with a generator to mimic the kite’s behaviour in wind conditions. Using MATLAB-SIMULINK, three different power ratings of 1 kW, 10 kW, and 100 kW systems were designed with a kite surface area of 2.5 m (Formula presented.), 14 m (Formula presented.), and 60 m (Formula presented.), respectively. The reel-out speed of the tether, tether force, traction power, drum speed, and drum torque were analysed for a wind speed range of 2 m/s to 12.25 m/s. The satellite wind speed data at 10 m and 50 m above ground with field data of the kite’s figure-of-eight trajectories were used to emulate the kite’s characteristics. The results of this study will promote the use of KAWECS, which can provide reliable and seamless energy flow, enriching wind energy exploitation under various installation environments. © 2023 by the authors.
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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