Faculty Publications
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Item Battery Storage-Based Novel Hybrid Islanding Detection Technique Using Lissajous Pattern Estimation(Institute of Electrical and Electronics Engineers Inc., 2022) Mondal, S.; Gayen, P.K.; Gaonkar, D.N.The reliability, uncertainty, and sensitivity of local islanding detection method for distributed generation (DG) system under diversified real-time scenarios and nonlinear loading conditions are not greatly explored. In this article, a new type hybrid islanding detection technique (IDT) is suggested, which reduces uncertainty and simultaneously improves reliability and sensitivity under different situations. In the technique, one detection parameter is defined, which is calculated from estimation of major and minor axes of Lissajous pattern (LP). Here, the evaluation of the parameter is done in two stages to avoid erroneous detection. In the first stage, the initiation of voltage transient is detected by LP. In the second stage, the active control via battery energy storage system (BESS) distinguishes nuisance tripping case from the islanding state. The extra active power injection/absorption via BESS also helps to identify islanding state at very near to zero power condition, i.e., sensitivity is enhanced. The detection time is found within 160 ms for different test cases, which is well below that of the acceptable upper value (2 s) specified in standard. The uncertainties in detection and threshold setting due to variations of harmonics and other operating conditions are removed in the proposed case, which is a distinct advantage. The Typhoon-HIL tool is used to carry out various case studies in real-time. Here, superior performances of proposed approach are observed in comparison with other state of the arts reported in the literature. © 1963-2012 IEEE.Item 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.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.Item 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