Jiefeng Hu

Virtual Flux Droop Method—A New Control Strategy of Inverters in Microgrids

The parallel operation of inverters in microgrids is mainly based on the droop method. The conventional voltage droop method consists of adjusting the output voltage frequency and amplitude to achieve autonomous power sharing without control wire interconnections. Nevertheless, the conventional voltage droop method shows several drawbacks, such as complicated inner multiloop feedback control, and most importantly, frequency and voltage deviations. This paper proposes a new control strategy in microgrid applications by drooping the virtual flux instead of the inverter output voltage. First, the relationship between the inverter virtual flux and the active and reactive powers is mathematically obtained. This is used to develop a new flux droop method. In addition, a small-signal model is developed in order to design the main control parameters and study the system dynamics and stability. Furthermore, a direct flux control algorithm is employed to regulate the virtual flux according to the droop controller, which avoids the use of proportional-integral controllers and pulse-width modulation modulators. Both the simulation and experimental results show that the proposed flux droop strategy can achieve active and reactive power sharing with much lower frequency deviation than the conventional voltage droop method, thus highlighting the potential use in microgrid applications.

Model Predictive Control of Grid-Connected Inverters for PV Systems With Flexible Power Regulation and Switching Frequency Reduction

This paper presents a model-predictive direct power control (MPDPC) strategy for a grid-connected inverter used in a PV system. Thus is aimed at use in distributed generation. The controller uses a system model to predict the system behavior at each sampling instant. The voltage vector generating least power ripples will then be selected according to a cost function and applied during the next sampling period, thus flexible power regulation can be achieved. In addition, the influences of one-step delay in digital implementation is investigated and compensated using a model based prediction scheme. Furthermore, a switching frequency reduction algorithm is developed by adding a nonlinear constraint to the cost function, which is a significant advantage in higher-power applications. The effectiveness of the proposed MPC strategy was verified numerically by using MATLAB/Simulink, and validated experimentally using a laboratory prototype.

Predictive Direct Virtual Torque and Power Control of Doubly Fed Induction Generators for Fast and Smooth Grid Synchronization and Flexible Power Regulation

Predictive direct torque control of the electric motors has been well developed. It is simple and has excellent steady state and transient performance. However, further developments are still under investigation for applications in the field of power generation. This paper presents a predictive direct virtual torque and power control strategy for a doubly fed induction generator, which allows fast and smooth grid synchronization, and flexible active and reactive power regulation. In the no-load mode, predictive direct virtual torque control is employed to meet the grid synchronization conditions. In the grid-connected mode, predictive direct power control is utilized to achieve flexible active and reactive power regulation. To simplify the control system structure and improve the reliability, a sensorless rotor position scheme is proposed. Furthermore, a model-based predictive scheme is introduced to compensate for a one-step delay in the digital implementation. The proposed control strategy is very simple and robust. There is constant switching frequency, while the requirement of smooth and fast grid synchronization is fulfilled. The transition from no load to flexible power regulation is achieved without changing the switching table. The proposed control strategy was tested by simulation using MATLAB/Simulink and experimentally validated on a 20-kW laboratory prototype.

Three-Vectors-Based Predictive Direct Power Control of the Doubly Fed Induction Generator for Wind Energy Applications

This paper proposes a simple but very effective method to achieve the predictive direct power control (PDPC) for doubly fed induction generator (DFIG)-based wind energy conversion systems. The novel approach is able to operate at low switching frequency and provides excellent steady-state and dynamic performances, which are useful for high-power wind energy applications. Three vectors are selected and applied during one control period to reduce both active and reactive power ripples. Compared to prior three-vectors-based art using two switching tables, the novel approach only needs one unified switching table to obtain the three vectors. Furthermore, the duration of each vector is obtained in a much simpler and straightforward way. The switching frequency can be significantly reduced by appropriately arranging the switching sequence of the three vectors. The influence of one step delay caused by digital implementation is also investigated. The possibility of operating the proposed PDPC under unbalanced grid voltage is also briefly discussed. The novel PDPC is compared with prior three-vectors-based art and its effectiveness is confirmed by the simulation results from a 2-MW-DFIG system and the experimental results from a scaled-down laboratory setup.

Predictive Direct Power Control of Doubly Fed Induction Generators Under Unbalanced Grid Voltage Conditions for Power Quality Improvement

This paper proposes a new control strategy of doubly fed induction generators (DFIGs) under unbalanced grid voltage conditions. The proposed controller includes a model predictive direct power control (MPDPC) method and a power compensation scheme. In MPDPC, the appropriate voltage vector is selected according to an optimization cost function, hence the instantaneous active and reactive powers are regulated directly in the stator stationary reference frame without the requirement of coordinate transformation, PI regulators, switching table, or PWM modulators. In addition, the behavior of the DFIG under unbalanced grid voltage is investigated. Next, a power compensation scheme without the need of extracting negative stator current sequence is developed. By combining the proposed MPDPC strategy and the power compensation scheme, distorted currents injected into the power grid by the DFIGs can be eliminated effectively.

Multi-Objective Model-Predictive Control for High-Power Converters

This paper presents a multi-objective model-predictive control (MOMPC) strategy for controlling converters in high-power applications. The controller uses the system model to predict the system behavior in each sampling interval for each voltage vector, and the most appropriate vector is then chosen according to an optimization criterion. By changing the cost function properly, multiobjectives can be achieved. To eliminate the influences of one step delay in digital implementation, a model-based prediction scheme is introduced. For high-power applications, the converter switching frequency is normally kept low in order to reduce the switching losses; this is done by adding a nonlinear constraint in the cost function. However, to avoid system stability deterioration caused by the low switching frequency, an N-step horizontal prediction is proposed. Finally, the control algorithm is simplified using a graphical algorithm to reduce the computational burden. The proposed MOMPC strategy was verified numerically by using MATLAB/Simulink, and validated experimentally using a laboratory ac/dc converter.

Robust Design Optimization of PM-SMC Motors for Six Sigma Quality Manufacturing

In our previous work, soft magnetic composite (SMC) material was employed to design cores for two kinds of permanent magnet (PM) motors, namely transverse flux machine (TFM) and claw pole motor. Compared with motors designed by traditional silicon steel sheets, these motors require 3D flux design with new material and new manufacturing method. Meanwhile, the performances of these motors highly depend on the material and manufacturing parameters besides structure parameters. Therefore, we present a robust design optimization method for high quality manufacturing of these PM-SMC motors to improve their industrial applications. Thereafter, from the design analysis of a PM-SMC TFM, it can be found that the proposed method can significantly improve the manufacturing quality and reliability of the motor, and reduce the manufacturing cost.

A New Control Method of Cascaded Brushless Doubly Fed Induction Generators Using Direct Power Control

Cascaded brushless doubly fed induction machines have attracted much attention because of the elimination of slip rings and brushes. However, only limited works have been reported on the control strategies due to the complex machine modeling. Further developments of these kinds of machines are still under investigation, especially for wind energy applications. This paper proposes a new control strategy for cascaded brushless doubly fed induction generators (CBDFIGs) based on direct power control. The effects of voltage vectors on the output active and reactive powers are first investigated. A vector selection strategy is then proposed to achieve flexible power regulation. In addition, the behaviors of the CBDFIG under unbalanced grid voltage conditions are studied and a power compensation scheme is developed to improve the power quality. The effectiveness of the proposed control strategy is validated experimentally on a laboratory prototype.

Multilevel Design Optimization of a FSPMM Drive System by Using Sequential Subspace Optimization Method

In our previous research, flux-switching permanent magnet machine (FSPMM) was investigated for the application in hybrid electric vehicles. To obtain the best performance of the whole drive system, a new multilevel design optimization method is presented for this kind of machine and a field oriented control system. The proposed multilevel optimization method is based on sequential subspace optimization method. In the implementation, three levels are employed to obtain the optimal design scheme at the system level. Meanwhile, sequential optimization method is employed to reduce the computation cost of finite element analysis on the motor level. Finally, from the design analysis, it can be found that the proposed method can provide design scheme with better performance, while the needed computation cost is reduced greatly for this FSPMM drive system.

Model predictive direct torque control for grid synchronization of doubly fed induction generator

A novel model predictive direct torque control (MPDTC) is proposed in this paper to achieve soft and fast grid synchronization for doubly fed induction generator (DFIG). This method is based on the direct control of a virtual torque and the rotor flux, which selects the optimal rotor voltage vector through an evaluation of a cost function. Neither PI regulator nor grid voltage measurement is needed for the MPDTC and only the information of grid voltage, rotor current and rotor position are necessary. The influence of one-step delay caused by digital implementation is also investigated in this paper. The MPDTC is compared with the switching-table-based direct torque control (STDTC) and exhibits better performance in terms of lower ripples in torque and flux, less rotor current harmonics and lower switching frequency. The presented simulation results verify the effectiveness of the novel method.