F.J. Maseda

Fault-Ride-Through Capability of Oscillating-Water-Column-Based Wave-Power-Generation Plants Equipped With Doubly Fed Induction Generator and Airflow Control

The increasing use of distributed power-generation systems, as with the case of wave-power-generation plants, requires a reliable fault-ride-through capability. The effects of grid fault include uncontrolled turbogenerator acceleration, dangerous rotor peak currents, and high reactive-power consumption so that the plant may contribute to the voltage dip. A simple solution is automatic disconnection from the grid, but this policy could lead to a massive power-network failure. This is why new Grid Codes oblige these systems to remain connected to the grid. In this paper, an oscillating-water-column-based wave-power-generation plant equipped with a doubly fed induction generator is modeled and controlled to overcome balanced grid faults. The improvement relies on the implementation of a control scheme that suitably coordinates the airflow control, the active crowbar, and the rotor- and grid-side converters to allow the plant to remain in service during grid fault, contributing to its attenuation by supplying reactive power to the network and complying with new Grid Code requirements. The simulated results show that it obtains a great reduction of the rotor currents, improving the transients and avoiding rotor acceleration. Similar results are obtained from the experimental implementation.

An adaptive sliding mode control law for induction motors using field oriented control theory

In this paper, an indirect field-oriented induction motor drive with a sliding-mode controller is presented. The proposed sliding-mode control law incorporates an adaptive switching gain that avoid calculating an upper limit of the system uncertainties. The design also includes rotor speed computation from measured stator terminal voltages and currents. The calculated speed is used as feedback in an indirect vector control system achieving the speed control without the use of shaft mounted transducers. Stability analysis based on Lyapunov theory is also presented, to guarantee the closed loop stability. Finally simulated results show on the one hand that the proposed controller with the proposed estimator provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances

Simple linear models for plasma control in tokamak reactors

The control of plasma in nuclear fusion has been revealed as a promising application of Control Engineering, with increasing interest in the control community during last years. In this paper it is outlined a control-oriented linear model for the control of plasma current. For this purpose, it is firstly provided a summary of the background necessary to deal with control problems in tokamak-based nuclear fusion reactors as it is the case of the future ITER tokamak. Besides, it is also given a review of the most used simulators and plasma models, with the aim of providing an adequate background for control engineers to derive their own control-oriented model or to choose the appropriate existing one. Finally, a simple linear model based on loop control voltage is derived.

Mathematical Modeling of Oscillating Water Columns Wave-Structure Interaction in Ocean Energy Plants

Oscillating Water Column (OWC)-based power take-off systems are one of the potential solutions to the current energy problems arising from the use of nuclear fission and the consumption of fossil fuels. This kind of energy converter turns wave energy into electric power by means of three different stages: firstly wave energy is transformed into pneumatic energy in the OWC chamber, and then a turbine turns it into mechanical energy and finally the turbogenerator module attached to the turbine creates electric power from the rotational mechanical energy. To date, capture chambers have been the least studied part. In this context, this paper presents an analytical model describing the dynamic behavior of the capture chamber, encompassing the wave motion and its interaction with the OWC structure and turbogenerator module. The model is tested for the case of the Mutriku wave power plant by means of experimental results. For this purpose, representative case studies are selected from wave and pressure drop input-output data. The results show an excellent matching rate between the values predicted by the model and the experimental measured data with a small bounded error in all cases, so that the validity of the proposed model is proven.

Stalling behaviour improvement by appropriately choosing the rotor resistance value in wave power generation plants

In this paper the performance of the Wells turbine has been improved, studying its stalling behaviour when the flow coefficient reaches a specific characteristic value. The generator increases its velocity when the flow coefficient of the turbine is approaching the critical point at which the turbine losses power.

Tokamak state-space control modeling

Nuclear fusion is nowadays one of the newest and most promising clean energies, composing a new application area of Control Engineering, with new and interesting challenges for the control community. In this sense, this paper deals with the modeling of tokamak nuclear fusion reactors. In order to control the creation of unstable modes in fusion processes, it is necessary to derive numerical models suitable for control strategies. The model presented addresses flux and energy conservation issues, discussing the mechanisms behind the creation of uncontrollable modes. The dynamics of the system is given by means of the energy functions which are solved for the currents in the structure, plasma current and plasma position. Thus, the equations for the state variables are derived based on the Hamiltonian equation of motion. In order to solve numerically, this model is linearised around an operation point by taking a Newton-Raphson step. Besides, the system output is completed by considering the equations for the flux and the poloidal field. Finally, the resulting low-order linear model is modified so as to obtain the corresponding state-space model which is verified by means of numerical simulations.

A robust field oriented control of induction motor with flux observer and speed adaptation

A new sensorless integral sliding mode control for induction motors which provides global asymptotic speed tracking in the presence of unknown parameters and load torque is presented. First, an improved method of speed estimation that operates on the principle of a speed adaptive flux and current observer has been proposed. An observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. Then a sliding mode controller with an integral switching surface is investigated. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances.

An active learning methodology in power electronic education

A novel educational methodology applied to power electronics applications is presented in this paper. A project-based learning and a specific scenario for promoting active learning in power electronic education are combined. The proposed scenario is a complete photovoltaic solar generation power system, designed for incorporating all basic power electronic conversions. The project-based learning methodology based on the functional dissection of power converters allows an efficient teamwork activity. The objective is to promote the transfer between theory and its real application. The methodology can be applied to large student groups. The performance of educational tools such as power electronics simulation software is improved.

Speed Sensorless Vector Control of Induction Motors Based on Robust Adaptive Variable Structure Control Law

A novel sensorless adaptive robust control law is proposed to improve the trajectory tracking performance of induction motors. The proposed design employs the so called vector (or field oriented) control theory for the induction motor drives and the designed control law is based on an integral sliding-mode algorithm that overcomes the system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances

An expert network for obtaining approximate discrete-time models for LTI systems under real sampling using parameter identification

In this paper, we present an expert scheme designed to obtain discrete transfer functions for LTI systems under real sampling of finite duration rather than an instantaneous ideal one. For this purpose, the expert network handles two different identification methods to derive parametric discrete models techniques of reduced mathematical complexity from measured input-output data series. One of the methods is based on a typically used least-squares minimization, while the other one is based on Leverriers algorithm; that is, using a data series of the impulse response of the system to identify a parametric discrete model. These techniques are of particular practical interest when the continuous-time system is unknown or when dealing with discrete-time systems whose analytical expression become very complex due, for instance, to the use of finite duration real sampling. The expert network improves the discretization process implementing a biestimation mechanism that switches to the model that provides a better performance at each considered estimation instant for different values of the hold order.