Debashisha Jena - Academia.edu (original) (raw)

Papers by Debashisha Jena

Research paper thumbnail of Semi-Г Type Single Phase Differential Boost Inverter With High Voltage Gain

IEEE Transactions on Circuits and Systems II: Express Briefs

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Machine learning based condition monitoring of a DC-link capacitor in a Back-to-Back converter

2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA)

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Comparative analysis of different machine learning techniques for condition monitoring of capacitors in a SEPIC converter

2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Improved Gamma type Y-source inverter for rooftop PV based V-G applications

International Journal of Electrical Power & Energy Systems

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Estimation of optimal number of components in Gaussian mixture model-based probabilistic load flow study

2016 IEEE Annual India Conference (INDICON), 2016

Gaussian mixture approximation (GMA)-based probabilistic load flow (PLF) is an efficacious approa... more Gaussian mixture approximation (GMA)-based probabilistic load flow (PLF) is an efficacious approach for quantifying the uncertainties associated with non-Gaussian and discrete input random variables (RVs). GMA approximates these input RVs by an equivalent weighted finite sum of Gaussian components. Expectation maximization (EM) algorithm is a well-established approach to estimate the parameters of the mixture components. The critical aspect is to know a priori the optimal number of components approximating the non-Gaussian distributions. The estimation of optimal number of parameters is essential because the parameters with inappropriate components may not evaluate the mixture model accurately. This paper adopts a cluster distortion function-based approach to determine the optimal number of mixture components. The k-means clustering result pertaining to that optimal number is then used for EM initialization. PLF using multivariate-GMA is performed on two IEEE test systems, considering various types of input RVs and their multiple correlations.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A low voltage harvesting in photovoltaic generation systems using negative embedded Z‐source inverter

International Transactions on Electrical Energy Systems, 2021

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

Advanced Robotics, 2016

Graphical Abstract In cold season, wet snow ice accretion on overhead transmission lines increase... more Graphical Abstract In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Power System Analysis Operation and Control

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Maximum power point tracking of PV array under non-uniform irradiance using artificial neural network

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015

This paper presents a maximum power point tracking (MPPT) method for tracking the global peak (GP... more This paper presents a maximum power point tracking (MPPT) method for tracking the global peak (GP) of photovoltaic (PV) array under non-uniform irradiance using artificial neural network (ANN). A feed forward multilayer perceptron model with Levenberg - Marquardt back propagation algorithm is used for tracking the global peak. The MPPT algorithm takes irradiance of PV modules as input and gives duty ratio of boost converter as output. The MPPT presented using ANN is compared with conventional hill climbing (HC) method and the actual values obtained from the P-V characteristics. Root Mean Square Error (RMSE) of PV array output power is calculated for both hill climbing method and proposed ANN method. Finally, a qualitative comparison is made between hill climbing method and ANN method.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Optimal GA based SMC with adaptive PID sliding surface for robot manipulator

2014 9th International Conference on Industrial and Information Systems (ICIIS), 2014

Different types of robotic manipulator controllers are developed to acquire dynamic properties an... more Different types of robotic manipulator controllers are developed to acquire dynamic properties and improve the global stability. In this paper a control strategy for robotic manipulator based on the coupling of the Artificial Neuro Fuzzy Inference System (ANFIS) with sliding mode control (SMC) approach has been presented. Initially, the Proportional Integral Derivative (PID) controller has developed for three different control strategies (IATE, ISE and ISTE) using GA. SMC has developed for best optimal criterion by using GA. The main objectives of these controller are to provide stability, good disturbance rejection and small tracking error. Finally, we have trained an ANFIS network, which can generate the adaptive PID control signal to the SMC of robot manipulator. The stability of the system is guaranteed by the checking of the Lyapunov stability theorem. Numerical simulations using the dynamic model of 2 DOF planner rigid robot manipulator with input torque disturbance shows the effectiveness in trajectory tracking problem and disturbance rejection. The simulation results of these controllers are compared with various torque disturbances in terms of path tracking and disturbance rejection. The proposed ANFIS adaptive SMC controller can achieve favorable tracking performance and it is robust with regard to disturbances in input torque.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A combined differential evolution and neural network approach to nonlinear system identification

TENCON 2008 - 2008 IEEE Region 10 Conference, 2008

This paper addresses the effectiveness of soft computing approaches such as Evolutionary Computat... more This paper addresses the effectiveness of soft computing approaches such as Evolutionary Computation (EC) and Artificial Neural Network (ANN) to system identification of nonlinear systems. In this work, three approaches namely a neuro-fuzzy, differential evolution (DE) and a combined DE-ANN have been applied for nonlinear system identification problem. Results obtained envisage that the proposed combined differential evolution-ANN approach to identification of nonlinear system exhibits better model identification accuracy and less computation time compared to the existing neural network approach and neuro-fuzzy technique (NFT).

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Backstepping Sliding Mode Control for variable speed wind turbine

2014 Annual IEEE India Conference (INDICON), 2014

This paper presents the nonlinear control for variable speed wind turbine (VSWT). The dynamics of... more This paper presents the nonlinear control for variable speed wind turbine (VSWT). The dynamics of the wind turbine (WT) are derived from the single mass model. The control objective is to maximize the energy capture from the wind with reduced oscillation on the drive train. The generator torque is considered as the control input and it depends on the optimal rotor speed which is derived from the effective wind speed. The effective wind speed is estimated from the aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR). Initially the conventional sliding mode controller (SMC) is considered. The control performance of SMC was compared with Backstepping Sliding Mode Control (BSMC) for different level of disturbance. The conventional SMC and proposed BSMC are tested with mathematical model and validated through the different mean wind speed. The result shows the better performance of BSMC and robustness to disturbances.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of ISMC based variable speed wind turbine for maximum power capture

Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC), 2014

This paper presents the nonlinear control for variable speed wind turbine (WT) where the dynamics... more This paper presents the nonlinear control for variable speed wind turbine (WT) where the dynamics of WT is derived from single mass model. The main objective is to maximize the energy capture from the wind and reduce the drive train oscillations. In order to control the WT the generator torque is considered as the control input. This torque depends on the optimal rotor speed derived from the effective wind speed. The effective wind speed is estimated from aerodynamic torque and rotor speed by using modified Newton Rapshon (MNR). The conventional techniques such as aero dynamic torque feed forward (ATF) & Indirect speed control (ISC) which does not depend on the effective wind speed, are unable to track the dynamic aspect of the WT. The other disadvantages of the above conventional methods are more power loss and not robust with respect to disturbances and uncertainties. To overcome these weaknesses nonlinear controllers are found to be more suitable than the conventional controller. In this paper a sliding mode control with integral action i.e. integral sliding mode controller (ISMC) is applied to the WT and a modified Newton Rapshon is used to estimate the effective wind speed. The result shows the significance improvement in proposed controllers compared with existing controllers.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Second order ISMC for variable speed wind turbine

2013 IEEE 8th International Conference on Industrial and Information Systems, 2013

ABSTRACT In this paper, a nonlinear controller is designed for variable speed wind turbine (WT) w... more ABSTRACT In this paper, a nonlinear controller is designed for variable speed wind turbine (WT) where the dynamics of the WT is derived for single mass model. The main aim of the controller is to extract the optimum power capture from the wind and minimize the transient load on low speed shaft. Modified Newton Rapshon (MNR) is used to estimate the effective wind speed and the optimal rotor speed is derived from it. The controller is used to track the optimal rotor speed by adjusting the generator torque which is acting as a control input to the WT. Existing controllers such as Nonlinear static state feedback with estimator (NSSFE) and Nonlinear dynamic state feedback with estimator (NDSFE) are unable to track the WT dynamics and introduces more transient on drive trains. In order to overcome the above drawbacks a nonlinear controller i.e. sliding mode control with integral action (ISMC) is used. In this paper an ISMC with MNR based wind speed estimator is used to control the single mass WT. The result shows the significance improvement in proposed controllers compared with NSSFE and NDSFE.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Nonlinear estimation and control of wind turbine

2013 IEEE International Conference on Electronics, Computing and Communication Technologies, 2013

ABSTRACT Wind energy is one of the major renewable energy sources which continue to be one of the... more ABSTRACT Wind energy is one of the major renewable energy sources which continue to be one of the fastest growing power generation sectors. For variable speed operation of wind energy conversion system, it is required to generate the maximum power at below the rated speed using an authentic and powerful control strategy. Wind speed has the major impact on the dynamics and control of wind turbines. But in practice there is no accurate measurement of effective wind speed available for direct measurement. In this paper a new technique is proposed for optimal power generation of wind turbine below rated speed without estimating the wind speed. An extended Kalman filter (EKF) is used to estimate the rotor speed and a proportional (P) controller is used to track the error between the measured and estimated rotor speed. The output of the P controller is the estimated aerodynamic torque. The estimated aerodynamic torque and the rotor speed act as an input to the aerodynamic torque feed-forward (ATF) controller. The output of the ATF controller is the generated torque. As the aerodynamic torque is highly dependent on the wind speed so it cannot be controlled. So we have to control the generated torque by using ATF for generating optimal power output. Finally the estimated outputs are validated through correlation analysis.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Nonlinear system identification using memetic differential evolution trained neural networks

Neurocomputing, 2011

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An Accurate Modeling of Photovoltaic System for Uniform and Non-Uniform Irradiance

International Journal of Renewable Energy Research

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Design, modeling and analysis of a new dual input-output switched capacitor converter

TENCON 2017 - 2017 IEEE Region 10 Conference, 2017

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Differential mode gamma source inverter with reduced switching stresses

2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2017

Impedance source inverters are covered with entire spectrum of power conversion process (dc-dc, d... more Impedance source inverters are covered with entire spectrum of power conversion process (dc-dc, dc-ac, ac-dc, and ac-ac). The traditional impedance source inverter suffers from high switching stresses and poor efficiency during high boost requirements. Compared to traditional impedance source inverters, the transformer based impedance source inverters are able to boost the output voltage gain and modulation index simultaneously with reduced passive components. The applications of transformer based gamma source impedance inverters are limited due to the difficulty in maintaining tight coupling, high instantaneous currents, increasing turn's ratio, high cost and large size. However, the gamma source inverter increases voltage gain by reducing turns ratio. This paper presents the operational modes of gamma source inverter in electric and magnetic domains, which helps the researchers to understand effects of transformer coupling in converter performance. In addition, the differential mode gamma source inverter is proposed that reduces the switching stresses. The operating principles of the proposed converter have been analyzed mathematically. Finally the theoretical analysis of proposed impedance inverter is validated by using MATLAB/SIMULINK.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An efficient hybrid technique for correlated probabilistic load flow study with photovoltaic generations

2016 National Power Systems Conference (NPSC), 2016

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Semi-Г Type Single Phase Differential Boost Inverter With High Voltage Gain

IEEE Transactions on Circuits and Systems II: Express Briefs

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Machine learning based condition monitoring of a DC-link capacitor in a Back-to-Back converter

2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA)

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Comparative analysis of different machine learning techniques for condition monitoring of capacitors in a SEPIC converter

2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Improved Gamma type Y-source inverter for rooftop PV based V-G applications

International Journal of Electrical Power & Energy Systems

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Estimation of optimal number of components in Gaussian mixture model-based probabilistic load flow study

2016 IEEE Annual India Conference (INDICON), 2016

Gaussian mixture approximation (GMA)-based probabilistic load flow (PLF) is an efficacious approa... more Gaussian mixture approximation (GMA)-based probabilistic load flow (PLF) is an efficacious approach for quantifying the uncertainties associated with non-Gaussian and discrete input random variables (RVs). GMA approximates these input RVs by an equivalent weighted finite sum of Gaussian components. Expectation maximization (EM) algorithm is a well-established approach to estimate the parameters of the mixture components. The critical aspect is to know a priori the optimal number of components approximating the non-Gaussian distributions. The estimation of optimal number of parameters is essential because the parameters with inappropriate components may not evaluate the mixture model accurately. This paper adopts a cluster distortion function-based approach to determine the optimal number of mixture components. The k-means clustering result pertaining to that optimal number is then used for EM initialization. PLF using multivariate-GMA is performed on two IEEE test systems, considering various types of input RVs and their multiple correlations.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A low voltage harvesting in photovoltaic generation systems using negative embedded Z‐source inverter

International Transactions on Electrical Energy Systems, 2021

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

Advanced Robotics, 2016

Graphical Abstract In cold season, wet snow ice accretion on overhead transmission lines increase... more Graphical Abstract In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Power System Analysis Operation and Control

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Maximum power point tracking of PV array under non-uniform irradiance using artificial neural network

2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), 2015

This paper presents a maximum power point tracking (MPPT) method for tracking the global peak (GP... more This paper presents a maximum power point tracking (MPPT) method for tracking the global peak (GP) of photovoltaic (PV) array under non-uniform irradiance using artificial neural network (ANN). A feed forward multilayer perceptron model with Levenberg - Marquardt back propagation algorithm is used for tracking the global peak. The MPPT algorithm takes irradiance of PV modules as input and gives duty ratio of boost converter as output. The MPPT presented using ANN is compared with conventional hill climbing (HC) method and the actual values obtained from the P-V characteristics. Root Mean Square Error (RMSE) of PV array output power is calculated for both hill climbing method and proposed ANN method. Finally, a qualitative comparison is made between hill climbing method and ANN method.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Optimal GA based SMC with adaptive PID sliding surface for robot manipulator

2014 9th International Conference on Industrial and Information Systems (ICIIS), 2014

Different types of robotic manipulator controllers are developed to acquire dynamic properties an... more Different types of robotic manipulator controllers are developed to acquire dynamic properties and improve the global stability. In this paper a control strategy for robotic manipulator based on the coupling of the Artificial Neuro Fuzzy Inference System (ANFIS) with sliding mode control (SMC) approach has been presented. Initially, the Proportional Integral Derivative (PID) controller has developed for three different control strategies (IATE, ISE and ISTE) using GA. SMC has developed for best optimal criterion by using GA. The main objectives of these controller are to provide stability, good disturbance rejection and small tracking error. Finally, we have trained an ANFIS network, which can generate the adaptive PID control signal to the SMC of robot manipulator. The stability of the system is guaranteed by the checking of the Lyapunov stability theorem. Numerical simulations using the dynamic model of 2 DOF planner rigid robot manipulator with input torque disturbance shows the effectiveness in trajectory tracking problem and disturbance rejection. The simulation results of these controllers are compared with various torque disturbances in terms of path tracking and disturbance rejection. The proposed ANFIS adaptive SMC controller can achieve favorable tracking performance and it is robust with regard to disturbances in input torque.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A combined differential evolution and neural network approach to nonlinear system identification

TENCON 2008 - 2008 IEEE Region 10 Conference, 2008

This paper addresses the effectiveness of soft computing approaches such as Evolutionary Computat... more This paper addresses the effectiveness of soft computing approaches such as Evolutionary Computation (EC) and Artificial Neural Network (ANN) to system identification of nonlinear systems. In this work, three approaches namely a neuro-fuzzy, differential evolution (DE) and a combined DE-ANN have been applied for nonlinear system identification problem. Results obtained envisage that the proposed combined differential evolution-ANN approach to identification of nonlinear system exhibits better model identification accuracy and less computation time compared to the existing neural network approach and neuro-fuzzy technique (NFT).

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Backstepping Sliding Mode Control for variable speed wind turbine

2014 Annual IEEE India Conference (INDICON), 2014

This paper presents the nonlinear control for variable speed wind turbine (VSWT). The dynamics of... more This paper presents the nonlinear control for variable speed wind turbine (VSWT). The dynamics of the wind turbine (WT) are derived from the single mass model. The control objective is to maximize the energy capture from the wind with reduced oscillation on the drive train. The generator torque is considered as the control input and it depends on the optimal rotor speed which is derived from the effective wind speed. The effective wind speed is estimated from the aerodynamic torque and rotor speed by using the modified Newton Rapshon (MNR). Initially the conventional sliding mode controller (SMC) is considered. The control performance of SMC was compared with Backstepping Sliding Mode Control (BSMC) for different level of disturbance. The conventional SMC and proposed BSMC are tested with mathematical model and validated through the different mean wind speed. The result shows the better performance of BSMC and robustness to disturbances.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of ISMC based variable speed wind turbine for maximum power capture

Proceedings of The 2014 International Conference on Control, Instrumentation, Energy and Communication (CIEC), 2014

This paper presents the nonlinear control for variable speed wind turbine (WT) where the dynamics... more This paper presents the nonlinear control for variable speed wind turbine (WT) where the dynamics of WT is derived from single mass model. The main objective is to maximize the energy capture from the wind and reduce the drive train oscillations. In order to control the WT the generator torque is considered as the control input. This torque depends on the optimal rotor speed derived from the effective wind speed. The effective wind speed is estimated from aerodynamic torque and rotor speed by using modified Newton Rapshon (MNR). The conventional techniques such as aero dynamic torque feed forward (ATF) & Indirect speed control (ISC) which does not depend on the effective wind speed, are unable to track the dynamic aspect of the WT. The other disadvantages of the above conventional methods are more power loss and not robust with respect to disturbances and uncertainties. To overcome these weaknesses nonlinear controllers are found to be more suitable than the conventional controller. In this paper a sliding mode control with integral action i.e. integral sliding mode controller (ISMC) is applied to the WT and a modified Newton Rapshon is used to estimate the effective wind speed. The result shows the significance improvement in proposed controllers compared with existing controllers.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Second order ISMC for variable speed wind turbine

2013 IEEE 8th International Conference on Industrial and Information Systems, 2013

ABSTRACT In this paper, a nonlinear controller is designed for variable speed wind turbine (WT) w... more ABSTRACT In this paper, a nonlinear controller is designed for variable speed wind turbine (WT) where the dynamics of the WT is derived for single mass model. The main aim of the controller is to extract the optimum power capture from the wind and minimize the transient load on low speed shaft. Modified Newton Rapshon (MNR) is used to estimate the effective wind speed and the optimal rotor speed is derived from it. The controller is used to track the optimal rotor speed by adjusting the generator torque which is acting as a control input to the WT. Existing controllers such as Nonlinear static state feedback with estimator (NSSFE) and Nonlinear dynamic state feedback with estimator (NDSFE) are unable to track the WT dynamics and introduces more transient on drive trains. In order to overcome the above drawbacks a nonlinear controller i.e. sliding mode control with integral action (ISMC) is used. In this paper an ISMC with MNR based wind speed estimator is used to control the single mass WT. The result shows the significance improvement in proposed controllers compared with NSSFE and NDSFE.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Nonlinear estimation and control of wind turbine

2013 IEEE International Conference on Electronics, Computing and Communication Technologies, 2013

ABSTRACT Wind energy is one of the major renewable energy sources which continue to be one of the... more ABSTRACT Wind energy is one of the major renewable energy sources which continue to be one of the fastest growing power generation sectors. For variable speed operation of wind energy conversion system, it is required to generate the maximum power at below the rated speed using an authentic and powerful control strategy. Wind speed has the major impact on the dynamics and control of wind turbines. But in practice there is no accurate measurement of effective wind speed available for direct measurement. In this paper a new technique is proposed for optimal power generation of wind turbine below rated speed without estimating the wind speed. An extended Kalman filter (EKF) is used to estimate the rotor speed and a proportional (P) controller is used to track the error between the measured and estimated rotor speed. The output of the P controller is the estimated aerodynamic torque. The estimated aerodynamic torque and the rotor speed act as an input to the aerodynamic torque feed-forward (ATF) controller. The output of the ATF controller is the generated torque. As the aerodynamic torque is highly dependent on the wind speed so it cannot be controlled. So we have to control the generated torque by using ATF for generating optimal power output. Finally the estimated outputs are validated through correlation analysis.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Nonlinear system identification using memetic differential evolution trained neural networks

Neurocomputing, 2011

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An Accurate Modeling of Photovoltaic System for Uniform and Non-Uniform Irradiance

International Journal of Renewable Energy Research

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Design, modeling and analysis of a new dual input-output switched capacitor converter

TENCON 2017 - 2017 IEEE Region 10 Conference, 2017

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Differential mode gamma source inverter with reduced switching stresses

2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2017

Impedance source inverters are covered with entire spectrum of power conversion process (dc-dc, d... more Impedance source inverters are covered with entire spectrum of power conversion process (dc-dc, dc-ac, ac-dc, and ac-ac). The traditional impedance source inverter suffers from high switching stresses and poor efficiency during high boost requirements. Compared to traditional impedance source inverters, the transformer based impedance source inverters are able to boost the output voltage gain and modulation index simultaneously with reduced passive components. The applications of transformer based gamma source impedance inverters are limited due to the difficulty in maintaining tight coupling, high instantaneous currents, increasing turn's ratio, high cost and large size. However, the gamma source inverter increases voltage gain by reducing turns ratio. This paper presents the operational modes of gamma source inverter in electric and magnetic domains, which helps the researchers to understand effects of transformer coupling in converter performance. In addition, the differential mode gamma source inverter is proposed that reduces the switching stresses. The operating principles of the proposed converter have been analyzed mathematically. Finally the theoretical analysis of proposed impedance inverter is validated by using MATLAB/SIMULINK.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An efficient hybrid technique for correlated probabilistic load flow study with photovoltaic generations

2016 National Power Systems Conference (NPSC), 2016

Bookmarks Related papers MentionsView impact