Jogendra Singh Thongam

Wind speed sensorless maximum power point tracking control of variable speed wind energy conversion systems

A maximum power point tracking (MPPT) controller for variable speed wind energy conversion system (WECS) is proposed. The proposed method, without requiring the knowledge of wind speed, air density or turbine parameters, generates at its output the optimum speed command for speed control loop of rotor flux oriented vector controlled machine side converter control system using only the instantaneous active power as its input. The optimum speed commands which enable the WE to track peak power points are generated in accordance with the variation of the active power output due to the change in the command speed generated by the controller. The concept is analyzed in a direct drive variable speed permanent magnet synchronous generator (PMSG) WECS with back-to-back IGBT frequency converter. Vector control of the grid side converter is realized in the grid voltage vector reference frame. Simulation is carried out in order to verify the performance of the proposed controller.

MPPT Control Methods in Wind Energy Conversion Systems

Wind energy conversion systems have been attracting wide attention as a renewable energy source due to depleting fossil fuel reserves and environmental concerns as a direct consequence of using fossil fuel and nuclear energy sources. Wind energy, even though abundant, varies continually as wind speed changes throughout the day. The amount of power output from a wind energy conversion system (WECS) depends upon the accuracy with which the peak power points are tracked by the maximum power point tracking (MPPT) controller of the WECS control system irrespective of the type of generator used. This study provides a review of past and present MPPT controllers used for extracting maximum power from the WECS using permanent magnet synchronous generators (PMSG), squirrel cage induction generators (SCIG) and doubly fed induction generator (DFIG). These controllers can be classified into three main control methods, namely tip speed ratio (TSR) control, power signal feedback (PSF) control and hill-climb search (HCS) control. The chapter starts with a brief background of wind energy conversion systems. Then, main MPPT control methods are presented, after which, MPPT controllers used for extracting maximum possible power in WECS are presented.

Control of variable speed wind energy conversion system using a wind speed sensorless optimum speed MPPT control method

This paper presents a wind speed sensorless maximum power point tracking (MPPT) controller for variable speed wind energy conversion systems (WECS). The proposed controller generates at its output the optimum speed (OS) command for the speed control loop of the vector controlled machine side converter control system without requiring the knowledge of wind speed. The MPPT control of the WECS is achieved using optimum speed-power curve of the WECS taking into account the variation of the system efficiency while operating at various operating points due to the change in wind speed. The method is based on the fact that the optimum output power of a WECS at a certain wind speed depends upon the total mechanical power developed by the turbine and efficiency of the WECS at the corresponding OS of rotation of the turbine. The controller algorithm implementation requires the knowledge of turbine parameters and output power and air density as its inputs. The proposed concept is analyzed in a variable speed direct drive permanent magnet synchronous generator (PMSG) WECS. Experimental results show good tracking capability of the proposed controller.

Artificial neural network-based maximum power point tracking control for variable speed wind energy conversion systems

A new maximum power point tracking (MPPT) controller using artificial neural networks (ANN) for variable speed wind energy conversion system (WECS) is proposed. The algorithm uses Jordan recurrent ANN and is trained online using back propagation. The inputs to the networks are the instantaneous output power, maximum output power, rotor speed and wind speed, and the output is the rotor speed command signal for the WECS. The network output after a time step delay is used as the feed-back signal completing the Jordan recurrent ANN. Simulation is carried out in order to verify the performance of the proposed algorithm.

Torque and pitch angle control for variable speed wind turbines in all operating regimes

In this paper, a multivariable control strategy is proposed for variable speed wind turbines operating in the two primary regimes, below-rated and above-rated wind speeds. A torque controller, based on the achievement of zero speed-tracking error, is developed to follow a trajectory that allows the wind turbine to operate with maximum power extraction in below-rated regime. The turbine torque is unknown to the controller, and its effect on it is compensated by estimation. In above-rated wind speed regime, a pitch angle controller is added to maintain a constant rated power, while the torque controller regulates the rotor speed to follow a constant nominal speed. The robustness of the control strategy is guaranteed through the incorporation of the turbine torque estimator. Simulation results demonstrate the effectiveness of the proposed control system for wind turbine operating in all wind speed regimes.

Adaptive sliding mode speed control for wind turbine systems

An adaptive sliding mode control strategy for speed tracking problem in variable speed wind turbine systems is presented in this work. The proposed adaptation strategy consists on updating the sliding gain and the turbine torque, which is considered unknown by the controller. The adaptation algorithms for the sliding gain and the torque estimation are carried out using the sliding surface to overcome the drawbacks of the conventional sliding mode control. The objective is to track a speed profile to operate the wind turbine in maximum power extraction. Simulation results are provided to validate the effectiveness of the proposed control system.

Neural network based wind speed sensorless MPPT controller for variable speed wind energy conversion systems

A wind speed sensorless neural network (NN) based maximum power point tracking (MPPT) control algorithm for variable speed wind energy conversion system (WECS) is proposed. The proposed method is developed using Jordan type recurrent NN which is trained online using back-propagation. The algorithm, without requiring the knowledge of wind speed, air density or turbine parameters, generates at its output the optimum speed command for the speed control loop of the vector controlled machine side converter control system using only the instantaneous power as its input. The output of the NN is fed into a state input after a unit step delay completing the Jordan type recurrent neural network. The proposed concept is analyzed in a grid connected direct drive variable speed permanent magnet synchronous generator (PMSG) WECS with a back-to-back frequency converter. Vector control of the grid side converter is realized in the grid voltage vector reference frame. Simulation is carried out in order to verify the performance of the proposed controller.

Trends in naval ship propulsion drive motor technology

Electric drive propulsion system for naval ships is a very active and fast-growing research area driven by the rapid growth in power electronics and advancement in machine design. Propulsion motors and associated drive control systems form the heart of modern all-electric ships (AES). This paper presents the technology trends in propulsion drive motors for AES propulsion systems. The induction motor (IM), permanent magnet synchronous motor (PMSM), the high temperature superconducting synchronous motor (HTSSM) and the superconducting homopolar DC motor (SHDCM) are examined. These machines are preferred over others mainly because of their higher power densities and efficiencies, allowing a more compact and efficient propulsion system design.

Nonlinear model predictive controller with state observer for speed sensorless induction generator–wind turbine systems

In this article, the problem of tracking control for variable speed induction generator–wind energy conversion system is investigated using nonlinear predictive control. A rotor speed predictive control algorithm has been designed to control the angular speed of the machine in order to allow the wind energy conversion system to operate with maximum power extraction. The generator torque and uncertainties are estimated and injected into the control law to improve the tracking performance. Control action is carried out assuming that all the states are known by measurement. Then, a state observer is implemented and Lyapunov method is used to prove the global stability of the complete continuous control scheme. Simulation is carried out to verify the performance of the proposed control system.

An optimum speed MPPT controller for variable speed PMSG wind energy conversion systems

A maximum power point tracking (MPPT) controller for variable speed permanent magnet synchronous generator (PMSG) wind energy conversion systems (WECS) is proposed. The proposed controller, without requiring the knowledge of wind speed, generates at its output, the optimum speed (OS) reference signal for the speed control loop of the vector controlled machine side converter control system, thus, allowing maximum power extraction. Optimum speed - power curve of the WECS, used by the controller, takes into account the changes in system efficiency while operating at different operating points due to the change in wind speed. The method proposed is based on the fact that the optimum output power of a WECS at a certain wind speed depends upon the total mechanical power developed by the turbine and efficiency of the WECS at the corresponding OS of rotation of the turbine. The controller requires the active power and air density as its inputs to generate optimum reference speed. The proposed controller is validated experimentally in a variable speed direct drive PMSG WECS using a wind turbine emulator.