This work proposes and experimentally verifies a novel virtual flux (VF) estimation method for the predictive control of back-to-back voltage-source power converters with a space vector modulator (SVM). The novelty of the proposed approach is the development of a time domain initial bias compensation virtual flux (IBC-VF) estimation method and its combination with a predictive control scheme with constant switching frequency. Theoretical analysis and implementation procedures of the proposed method are developed in detail. Compared to two conventional bandpass filter-based VF estimation methods, the proposed IBC-VF method shows a much faster dynamic response. The whole IBC-VF-based predictive control scheme is realized in the $\alpha\beta$ frame and so does not require Park's transformation. The proposed control scheme is implemented on a commercial off-the-shelf field-programmable-gate-array-based platform. By using a single-cycle timed loop (SCTL) technique, the whole computation is finished within 2.6 $\mu\hbox{s} $ , making the compensation of the calculation time obsolete. Both simulation and experimental results emphasize the effectiveness of the proposed scheme.

Predictive Control With Novel Virtual-Flux Estimation for Back-to-Back Power Converters

Three-Phase Voltage Source Converters (VSCs) are finding widespread applications in grid integrated power conversion systems. The control systems of such VSCs are in an increasing number of these a ...

Control of Grid Integrated Voltage Source Converters under Unbalanced Conditions : Development of an On-line Frequency-adaptive Virtual Flux-based Approach

Design optimization of PM couplings using hybrid Particle Swarm Optimization-Simplex Method (PSO-SM) Algorithm

MODELING AND CONTROL OF A DOUBLY-FED INDUCTION GENERATOR FOR WIND TURBINE-GENERATOR SYSTEMS Xin Jing, M.S.E.E Marquette University, 2012 Wind energy plays an increasingly important role in the world because it is friendly to the environment. During the last decades, the concept of a variable-speed wind turbine (WT) has been receiving increasing attention due to the fact that it is more controllable and efficient, and has good power quality. As the demand of controllability of variable speed WTs increases, it is therefore important and necessary to investigate the modeling for wind turbine-generator systems (WTGS) that are capable of accurately simulating the behavior of each component in the WTGS. Therefore, this thesis will provide detailed models of a grid-connected wind turbine system equipped with a doubly-fed induction generator (DFIG), which includes the aerodynamic models of the wind turbine, the models of the mechanical transmission system, the DFIG models and the three-phase two-level PWM voltage source converter models. In order to obtain satisfying output power from the WTGS, control strategies are also necessary to be developed based on the previously obtained WTGS models. These control schemes include the grid-side converter control, the generator-side converter control, the maximum power point tracking control and the pitch angle control. The grid-side converter controller is used to keep the DC-link voltage constant and yield a unity power factor looking into the WTGS from the grid-side. The generator-side converter controller has the ability of regulating the torque, active power and reactive power. The maximum power point tracking control is used to provide the reference values for the active power at the stator terminals. The pitch angle control scheme is used to regulate the pitch angle and thus keep the output power at rated value even when the wind speed experiences gusts. Various studies in the literature have reported that two-level converters have several disadvantages compared with three-level converters. Among the disadvantages are high switching losses, high dv/dt, and high total harmonic distortion (THD). Hence, the models and field oriented control schemes for three-level neutral-point-clamped (NPC) converters are also investigated and applied to a WTGS. Besides, an advanced modulation technology, namely, space vector PWM (SVPWM), is also investigated and compared to traditional sinusoidal PWM in a WTGS.

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Modeling and control of a doubly-fed induction generator for wind turbine-generator systems

Cost Reduction of Permanent Magnet Synchronous Machines

The objective of this paper is to optimize the structural parameters of the Permanent Magnet Drive by minimizing the manufacturing costs while maintaining the output performance. The electromagnetic analysis of the Permanent Magnet Drive is carried out by the Finite Element Method. In order to debasing the cost of calculation and time, the rapid calculation model which can map the relationship between the structural parameters and output torque is established by the Artificial Neural Network. The sample data for training are obtained by combining the Finite Element Method with the Orthogonal Test Design. The purpose of optimization is gained by using the Particle Swarm Optimization, and then the output performance of the new designs is calculated and compared with that of the orthogonal optimization. The results show that the new design obtained from the optimal method proposed in this paper has a reduction of approximately 20% in the magnet material but in the mean time with no loss of the output torque.

Structural Optimization of the Permanent Magnet Drive Based on Artificial Neural Network and Particle Swarm Optimization

This paper presents a novel decoupling control strategy for three-level NPC PWM rectifier without line voltage sensors, combining virtual flux oriented control (VOFC) with traditional direct current control based on the decoupled d-q frame. A virtual flux linkage vector can be constructed similarly to the observation of AC motor flux linkage, which may serve as the oriented vector in the vector control of the PWM rectifier instead of the line voltage vector. As a result, the AC voltage sensors and phase locked circuit will be eliminated and the costs of PWM rectifier can be reduced. According to the design principle of AC motor flux observer, a modified virtual grid flux observer and the grid voltage estimation method are proposed, which solves the DC drift problem caused by a wrong initial value selecting of integer in virtual flux oriented vector control for PWM rectifier. Finally based on Matlab/Simulink, this paper constructs virtual flux oriented current decoupling control simulation model of three-level PWM rectifier without grid voltage sensor. The reliability of the observer has been proved. The good dynamic and static performances of the control scheme have been showed by simulation.

Study of the Control System of Three-Level PWM Rectifier Based on Virtual Flux Oriented

The Permanent Magnet Drive is a new kind of advanced energy-saving products with disc structure. This paper mainly aims at nonlinear regression modeling of the Permanent Magnet Drive with BP neural network, adaptive network-based fuzzy inference system and support vector machine. The sample points for training are the electromagnetic characteristics of the Permanent Magnet Drive and obtained from finite element method simulation. The accuracy, validity and prediction capability of these three modeling methods are verified and compared. Simulation results prove that, all approaches have highly precise, little time consuming for convergence and strong prediction performance, and support vector machine reflects the characteristics of the Permanent Magnet Drive best. The nonlinear models built in this paper provide effective tools for the performance analysis, the control system establishment and the optimization design of the Permanent Magnet Drive.

Chenglong Shi

Papers

Structural Optimization of the Permanent Magnet Drive Based on Artificial Neural Network and Particle Swarm Optimization

Study of the Control System of Three-Level PWM Rectifier Based on Virtual Flux Oriented

Study on nonlinear regression modeling methods of the Permanent Magnet Drive