Browsing by Author "Aanchal Verma"

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An accurate parameters identification of solar PV models using a modified exponential distribution optimization
(Springer Science and Business Media Deutschland GmbH, 2024) Ayyarao S. L. V. Tummala; Baseem Khan; Ahmed Ali; Aanchal Verma; M.P.S. Chawla
This paper presents a new metaheuristic algorithm called Exponential Distribution Optimization, which is based on mathematics and can effectively identify parameters for a solar photovoltaic (PV) mathematical model that closely approximates a real-life PV cell or module. The algorithm works in tandem with the Newton–Raphson method to address nonlinear equations, generating an objective function that minimizes the root mean square error (RMSE) between experimentally measured and estimated currents. To improve its convergence capability, the algorithm incorporates a nonlinear weight updating mechanism that adjusts the weights assigned to each member during the optimization process and this adaptive mechanism enables the algorithm to efficiently converge to the global optimal solution. The proposed approach is evaluated using two widely recognized benchmark models, and its performance is compared with that of other recent and contemporary algorithms in the literature. The proposed algorithm, modified Exponential Distribution Optimization Algorithm (mEDOA) achieves an RMSE values of 7.7298E-04 for the single diode PV model, 7.444E-04 for the double diode PV model and 7.3531E-04 for the triple diode PV model. The evaluation results demonstrate that the mEDOA surpasses other algorithms in consistency, accuracy, robustness, and speed. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
An accurate parameters identification of solar PV models using a modified exponential distribution optimization
(Springer Science and Business Media Deutschland GmbH, 2025) Tummala S.L.V. Ayyarao; B. Khan; Ahmed Abdi Yusuf Ali; Aanchal Verma; Manendrapal Singh S. Chawla
This paper presents a new metaheuristic algorithm called Exponential Distribution Optimization, which is based on mathematics and can effectively identify parameters for a solar photovoltaic (PV) mathematical model that closely approximates a real-life PV cell or module. The algorithm works in tandem with the Newton–Raphson method to address nonlinear equations, generating an objective function that minimizes the root mean square error (RMSE) between experimentally measured and estimated currents. To improve its convergence capability, the algorithm incorporates a nonlinear weight updating mechanism that adjusts the weights assigned to each member during the optimization process and this adaptive mechanism enables the algorithm to efficiently converge to the global optimal solution. The proposed approach is evaluated using two widely recognized benchmark models, and its performance is compared with that of other recent and contemporary algorithms in the literature. The proposed algorithm, modified Exponential Distribution Optimization Algorithm (mEDOA) achieves an RMSE values of 7.7298E-04 for the single diode PV model, 7.444E-04 for the double diode PV model and 7.3531E-04 for the triple diode PV model. The evaluation results demonstrate that the mEDOA surpasses other algorithms in consistency, accuracy, robustness, and speed. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
Design and dynamic analysis of superconducting magnetic energy storage-based voltage source active power filter using deep Q-learning
(Springer Science and Business Media Deutschland GmbH, 2024) M. Mangaraj; Ramana Pilla; Polamarasetty P. Kumar; Ramakrishna S. S. Nuvvula; Aanchal Verma; Ahmed Ali; Baseem Khan
The voltage source active power filter (VS-APF) is being significantly improved the dynamic performance in the power distribution networks (PDN). In this paper, the superconducting magnetic energy storage (SMES) is deployed with VS-APF to increase the range of the shunt compensation with reduced DC link voltage. The proposed SMES is characterized by the physical parameter, inductive coil, diodes and insulated gate bipolar transistors (IGBTs). The deep Q- learning (DQL) algorithm is suggested to operate SMES based VS-APF for the elimination of harmonics under different loading scenarios. Apart from this, the other benefits like improvement in power factor (PF), load balancing, potential regulation are attained. The simulation studies obtained from the proposed method demonstrates the correctness of the design and analysis compared to the VS-APF. To show the power quality (PQ) effectiveness, balanced and unbalanced loading are considered for the shunt compensation as per the guidelines imposed by IEEE-519-2017 and IEC-61000-1 grid code by using dSPACE-1104-based experimental study. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023.
Optimization of Transmitter Semi-Angle and Ambient Noise Cancellation for Indoor Visible Light Communications
(Greater Mekong Subregion Academic and Research Network, Asian Institute of Technology, 2023) Aanchal Verma; Amritanshu Pandey
Visible light communication (VLC) is unquestionably a viable method for dealing with the ever-increasing traffic on wireless networks. Light-emitting diodes (LEDs), which are used for lighting, can be used to convey high-speed data. The optical power determines the indoor VLC link performance. A fundamental challenge in this regard is to design an optimized design of visible light communication with the uniform power distribution and minimize the interference of the ambient light in the daytime. The optimization of transmitter semi-angle and ambient noise cancellation for indoor visible light communications is discussed in this study. The study shows that lowering the semi-angle improves average received optical power while raising power fluctuations on the receiver's plane. In order to resolve this trade-off, we use a unique and simple optimization method for calculating the appropriate transmitter semi-angle that maximizes received power while reducing power variation around the room. By adjusting the number of LED panels and their placements on the plane of the transmitter, the best configuration based on the optimization function is selected. The effects of utilizing a differential optical receiver on SNR distribution in optimal VLC indoor configuration is discussed, which results in better SNR, and the ability to suppress ambient light and other atmospheric noise. © 2023. All Rights Reserved.