Browsing by Author "Dhar, Rupak Kanti"

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Citation - WoS: 19
Citation - Scopus: 24
Bacteria Foraging Optimisation Algorithm Based Optimal Control for Doubly-Fed Induction Generator Wind Energy System
(INST ENGINEERING TECHNOLOGY-IET, 2020) Bakır, Hale; Merabet, Adel; Dhar, Rupak Kanti; Kulaksız, Ahmet Afşin
In this study, an optimisation method, based on bacteria foraging, is investigated to tune the parameters of the proportional-integral (PI) controllers in a doubly-fed induction generator (DFIG) wind energy system connected to the grid. The generator is connected to the grid directly at the stator and through the back-to-back converter at the rotor. The control system includes PI controllers, at the rotor side, to regulate the rotor currents and PI controller to regulate the dc-link voltage for efficient power transfer. The control parameters, of three PI controllers, are optimised offline using the bacteria foraging optimisation algorithm and a modelled DFIG wind energy system. Various performance criteria, based on the tracking errors, are used to assess the efficiency of the optimisation method. Furthermore, the conventional tuning method and genetic algorithm optimisation method are conducted and compared to the bacteria foraging optimisation method to demonstrate its advantages. The optimised control parameters are evaluated on a DFIG wind energy experimental setup. Experimental and simulation results are provided to validate the effectiveness of each optimisation method.
Citation - WoS: 12
Citation - Scopus: 15
Experimental Evaluation of Water Cycle Technique for Control Parameters Optimization of Double-Fed Induction Generator-Based Wind Turbine
(ELSEVIER - DIVISION REED ELSEVIER INDIA PVT LTD, 2021) Bakır, Hale; Merabet, Adel; Dhar, Rupak Kanti; Kulaksız, Ahmet Afşin
In this paper, a nature-inspired optimization algorithm is employed for parametric tuning of proportional-integral controllers in the vector control of a grid-linked doubly-fed induction generator energy system. The optimization approach is based on the nature-inspired computing technique from the water cycle. The vector control system includes loops for dc-link voltage control at the grid side converter and the rotor current at the rotor side converter. The water cycle optimization is implemented to tune six control parameters by minimizing a cost function carried out using the tracking errors. The cost function value, required in the optimization process, is carried out from a simulated grid-linked doubly fed induction generator energy system. The optimized control parameters are tested on an experimental setup. Experimental results, obtained for a grid-linked doubly-fed induction generator energy system in terms of different optimization methods and conditions, are provided to demonstrate the effectiveness of water cycle optimization technique. As a result of the comparative analysis, it is observed that water cycle technique offers better results in minimizing the overshoot and the response time. (C) 2021 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Citation - WoS: 15
Citation - Scopus: 19
Implementation of Water Cycle Optimization for Parametric Tuning of Pi Controllers in Solar Pv and Battery Storage Microgrid System
(Ieee-Inst Electrical Electronics Engineers Inc, 2022) Dhar, Rupak Kanti; Merabet, Adel; Bakir, Hale; Ghias, Amer M. Y. M.
In this article, a nature-inspired optimization method, based on the water cycle, is implemented for optimal control of a solar photovoltaic microgrid with battery storage. The water cycle optimization is used to tune the parameters of the proportional-integral controllers in the regulation of the battery current and the dc-link voltage. In order to implement the optimization algorithm, the microgrid model is developed and simulated to carry out the cost function to be minimized in the optimization process. The optimization is conducted using different performance indices. The optimized control parameters are validated on a simulated microgrid and an experimental setup. Simulation and experimental results are provided and compared to genetic algorithms and a conventional tuning method to demonstrate the effectiveness of the water cycle technique.