Faculty Publications
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Item Performance analysis of automated quantitative feedback theory based robust controller for photovoltaic converter(Institute of Electrical and Electronics Engineers Inc., 2018) Gudimindla, H.; Manjunatha Sharma, K.M.Robust controller design for photovoltaicconverters (PVC) has received considerable critical attention due to solar panels operated under uncertain environmental circumstances. This paper presents automated loop-shaping based robust controller design for PVC voltage regulation with the aid of quantitative feedback theory (QFT) using Genetic algorithm. The step by step design guidelines for the automated QFT (AQFT) robust controller is deliberated in detail. The proposed AQFT controller exhibits decreasing modular plot, descending phase response and nearer to the universal bound to replicate the controller ideal characteristics. Finally, benchmarking of the proposed controller with affine parameterization design method available in the literature is performed through simulations. © 2018 IEEE.Item Performance analysis of automated QFT robust controller for long-term grid tied PV simulations(Institute of Electrical and Electronics Engineers Inc., 2020) Gudimindla, H.; Krishnamurthy, M.S.; Sandhya, S.Long-term simulations are significant to understand the real-time operation of grid-tied renewable energy system configurations. Grid-tied photovoltaic system (GPV) is highly non-linear due to the dependency of real-time meteorological conditions. The non-linear behavior of the photovoltaic (PV) system with the power electronic converter makes the long-term simulation inefficient and slow. This paper presents an efficient and simple modelling approach for GPV modelling suitable for long-term simulations. The recent advancements in control strategies and system configurations, sub-module level controller operation gained much interest but the simulation of such systems can be very challenging due to a large number of power electronic components and their control, non-linear behavior of PV system. This paper proposed a genetic algorithm based robust controller design in the quantitative feedback theory (QFT) framework to extract the maximum power from GPV at the sub-module level to extradict the power losses due to partial shading conditions. The performance of the proposed controller at the PV sub-module level is evaluated through comparison with the Q-parameterization based controller. The proposed QFT methodology based robust controller is shown to have advantages over Q-parameterization approach to simulate long-term GPV operation. © 2020 IEEE.Item Performance Analysis of Adaptive Speed Reference Tracking QFT Robust Controller for Three Phase Grid connected Wind Turbine under Stochastic Wind Speed Conditions(Institute of Electrical and Electronics Engineers Inc., 2021) Gudimindla, H.; Manjunatha Sharma, K.; Sandhya, S.Due to stochastic nature of wind, stator current harmonics arise in PMSG based wind energy conversion system that causes the oscillations in wind turbine shaft. These oscillations shows adverse effect on lifespan of wind turbine. It is desirable to track the speed reference in grid connected variable speed wind system along with the maximum power extraction. In this sense, this paper presents the robust controller design methodology to achieve the reference speed tracking controller with maximum power extraction capability in variable speed PMSG driven wind turbines. Further, A modified fitness function is introduced to design the automated robust controller using Genetic algorithm in quantitative feedback theory framework. MATLAB simulations are performed on 20 kW three phase grid connected wind system to analyse the dynamic performance of proposed robust controller under step variation and stochastic wind speed conditions. It is evident from the simulations that tracking of reference speed is achieved with proposed controller under power injecting to load and power sharing with grid conditions. © 2021 IEEE.Item Performance analysis of Grid Integrated Hybrid Renewable Energy System configuration application to Residential Buildings(Institute of Electrical and Electronics Engineers Inc., 2021) Gudimindla, H.; Manjunatha Sharma, K.; Sandhya, S.Recent technological advancements and cost reduction drives increasing the penetration of renewable energy sources with grid. Utilisation factor of renewable energy sources is low due to dependency on the environmental conditions. Basically, hybrid energy systems provide constant, high-quality power for the remote communities. The sizing of the hybrid system is significant to meet the load demand of residential buildings. In this paper, A simple optimal sizing algorithm is used to model the Wind turbine and PV system to meet the residential load. Quantitave feedback theory (QFT) based robust controller is implemented for the proposed sub-module integrated PV converter and the PMSG based wind energy conversion system to extract maximum power using simple genetic algorithm. Performance of the QFT controller is analysed through MATLAB simulations under varying irradiance and wind conditions. © 2021 IEEE.Item Accurate parametrization and methodology for selection of pertinent single diode photovoltaic model with improved simulation efficiency(Elsevier Ltd, 2018) Gudimindla, H.; Sharma K, M.An accurate model of photovoltaic (PV) panel is indispensable for simulations studies. In general, the PV circuit parameters for simulation studies are extracted from the manufacturer's data sheet under different environmental conditions. The PV characterizing equations are nonlinear and requires a more involved computation. This paper presents a fast convergent third order Newton-type method to solve such nonlinear equations and thereby, to accurately parameterize any of the possible PV circuit models. The applicability and suitability of the proposed method are demonstrated through modeling of multi and mono-crystalline PV cells. Further an algorithm to evaluate the efficacy of the available methods and the proposed method is presented. PV characteristics of the suitable circuit model at various levels of temperature and irradiation are also examined. Finally, the effectiveness of the developed method is comprehensively assessed through comparison with the most recent and available effective techniques by considering various performance indices based on current-voltage, power-voltage curves and experimental data is carried out. © 2018 Elsevier LtdItem Dynamic performance evaluation of automated QFT robust controller for grid-tied fuel cell under uncertainty conditions(Elsevier Ltd, 2020) Gudimindla, H.; K, M.S.Power flow control and peak point tracking are significant in grid-tied renewable energy systems to improve power factor and efficient energy extraction. In this paper, the design of robust controllers for the power electronic converters of the grid-connected PEM fuel cell with thermal modeling is deliberated. Further, the transfer function model of the power electronic converters is derived by considering uncertainty in system parameters. A low complexity algorithm is used to design the converter parameters from the uncertainty range. The proposed robust automated power flow controller is designed to minimize the objective function using a genetic algorithm in the quantitative feedback theory framework. The robustness and disturbance rejection with enhanced transient response of the proposed controller is evaluated under heavy and light loading conditions, DC-link voltage and grid voltage distortion uncertainty conditions are investigated. Finally, comprehensive simulations are performed to validate the proposed controller performance with the existing controller under the above-mentioned uncertainty conditions. © 2020 Elsevier Ltd