Faculty Publications
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Item Steady-state Initialization of Doubly Fed Induction Generator Based Wind Turbine Considering Grid Side Filter(IEEE Computer Society, 2021) Karthik, D.R.; Kotian, S.M.; Manjarekar, N.S.In this paper, a steady-state initialization method for a doubly fed induction generator (DFIG) based wind turbines including grid side (GS) filter equations is discussed. The approach employed considers factors like non-zero grid side converter (GSC) reactive power and GS filter losses. As per the recent grid code requirements, DFIG should be able to participate in reactive power support to maintain voltage stability during faults. Also GSC acts as STATCOM by its structure and supports in damping inter-area oscillations. Above conditions mandates to consider the non-unity power factor operation of GSC. The approach employed also considers GS filter losses, by which an accurate initial values can be obtained. Dynamic evaluation of the steady-state values obtained are performed using eigenvalues and time-domain simulations. The studies are performed on a single-machine-infinite-bus (SMIB) system and the results are compared with dynamic results with a case wherein GS currents are considered as dummy states. © 2021 IEEE.Item An Accurate Method for Steady State Initialization of Doubly Fed Induction Generator(Institute of Electrical and Electronics Engineers Inc., 2022) Karthik, D.R.; Kotian, S.M.; Manjarekar, N.S.In this paper, an accurate method for calculation of steady-state values of a doubly fed induction generator (DFIG) is proposed. The assumption of active power (P) and reactive power (Q) or terminal voltage (Vt) as constant variables at DFIG bus may not yield accurate results as wind speed is variable in nature. So, an initialization strategy considering input wind speed (Vw) as known variable, is employed in the present work, which is an accurate way to start with initialization. The approach followed in this paper also considers grid side filter losses, and non-zero reactive power flow through grid side converter (GSC). The steady-state values obtained from the approach followed in this paper is dynamically tested on SMIB system by conducting modal studies and time domain simulations. © 2022 IEEEItem A Comparison Study of the Classical and Modern Results of Semi-Local Convergence of Newton-Kantorovich Iterations(MDPI, 2022) Regmi, S.; Argyros, I.K.; George, S.; Argyros, C.I.There are a plethora of semi-local convergence results for Newton’s method (NM). These results rely on the Newton–Kantorovich criterion. However, this condition may not be satisfied even in the case of scalar equations. For this reason, we first present a comparative study of established classical and modern results. Moreover, using recurrent functions and at least as small constants or majorant functions, a finer convergence analysis for NM can be provided. The new constants and functions are specializations of earlier ones; hence, no new conditions are required to show convergence of NM. The technique is useful on other iterative methods as well. Numerical examples complement the theoretical results. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Item Local Convergence of Traub’s Method and Its Extensions(MDPI, 2023) Saeed K, M.; Remesh, K.; George, S.; Padikkal, P.; Argyros, I.K.In this article, we examine the local convergence analysis of an extension of Newton’s method in a Banach space setting. Traub introduced the method (also known as the Arithmetic-Mean Newton’s Method and Weerakoon and Fernando method) with an order of convergence of three. All the previous works either used higher-order Taylor series expansion or could not derive the desired order of convergence. We studied the local convergence of Traub’s method and two of its modifications and obtained the convergence order for these methods without using Taylor series expansion. The radii of convergence, basins of attraction, comparison of iterations of similar iterative methods, approximate computational order of convergence (ACOC), and a representation of the number of iterations are provided. © 2023 by the authors.