Model Predictive Control of Three-Phase Voltage Source Rectifiers under Unbalanced Grid Voltage Conditions

This study proposes a model predictive stator current control (MPSCC) strategy of doubly fed induction generator (DFIG) under unbalanced grid voltage conditions. Sinusoidal and balanced stator currents injected into the power grid can be ensured due to the direct control of stator currents rather than rotor currents. Model predictive control instead of traditional vector control is adopted, which can increase the current loop bandwidth and obtain faster dynamic responses. Conventional resonant regulators such as second‐order generalised integrators or second‐order vector integrators that are usually used to eliminate unbalanced components in stator currents can also be avoided. Moreover, both extractions of negative sequence components in rotor or stator currents and calculation of commanded rotor current are avoided, which simplifies the control scheme. The proposed MPSCC strategy can also implement the grid connection by introducing the virtual stator currents without any changes in the control scheme. Finally, experimental results based on a 1 kW lab DFIG system are provided to validate the effectiveness of the proposed control strategy.

Unbalanced grid is a normal fault in power system, and in order to ensure the rectifier current tracking precision under this condition, the design and implementation of rectifier control strategies become more complex. In view of this, a simplified grid current tracking strategy is proposed, which is suitable for LCL-based rectifier operating in both balanced and unbalanced conditions. The grid current sinusoidal is achieved by tracking converter-side current of LCL filter. The current reference is only calculated by grid voltage and its 1/4 period lagging signal at stationary coordinates. Compared with conventional strategies, sequence separation and Phase-Locked Loop (PLL) are avoided. Besides, an improved active damping method is applied, which can accurately extract harmonic voltage and enhance the resonance suppressing effect. Simulation and experimental results verify the effectiveness of the proposed strategy.

Model predictive direct power control for modular multilevel converter under unbalanced conditions with power compensation and circulating current reduction

When a modular multilevel converter (MMC) operates under unbalanced grid voltage conditions, it generates positive-sequence, negative-sequence, and zero-sequence components in the arm currents, which increase system losses and disrupt normal operation. To tackle this problem, this paper introduces a method that employs a second-order generalized integrator (SOGI) to extract the second- and fourth-frequency components from the arm currents. Subsequently, an enhanced quasi-proportional integral resonant (PIR) controller is applied to individually suppress these circulating currents. The approach is validated through MATLAB simulations. The results demonstrate that the proposed suppression method quickly reduces the secondand fourth-frequency circulating currents and significantly minimizes submodule voltage fluctuations, confirming its effectiveness under unbalanced grid conditions.

Model predictive control (MPC) is an efficient and growing approach to power converter control. This paper proposes an improved and simplified model predictive current control (MPCC) technique for a four-level nested neutral point clamped (4L-NNPC) converter. Conventional MPCC exhibits better performances as compared to the conventional linear control system such as fast dynamic response, consideration of the system constraints, and nonlinearities. However, the application of the conventional model predictive current control (MPCC) approach on complex systems provokes a significant number of calculations, which is the main hurdle to its practical implementation. To fix this flaw, this paper proposes an effective algorithm to shorten the execution time of the conventional MPCC. In this proposed technique, 216 current predictions of the conventional MPCC are skipped and converted into one required voltage vector (RVV) prediction. With this equivalent reference voltage transformation, the calculation burden of MPCC is significantly reduced, while the output performance is not influenced. The results of the simplified MPCC for the 4L-NNPC converter are analyzed and compared with the conventional MPCC. The computational time is reduced by 19.56% using the simplified MPCC, while keeping an approximately similar error of output currents. The switching frequency and total harmonic distortion (THD) of the proposed method are reduced by 8.16% and 0.07%, respectively, as compared to the conventional technique. These results demonstrate the fact that that the performance of a conventional MPCC is enhanced with the proposed MPCC. The proposed algorithm can be applied to several inverter topologies.

Conventional model predictive current control (MPCC) applies only one vector during one control period, which produces large torque and flux ripples and high current harmonics in permanent magnet synchronous motor (PMSM) drives. Recently MPCC with duty cycle control has been proposed to improve the steady state performance by applying one non-zero vector and one null vector during one control period. However, the prior method requires lots of calculations and predictions to find the optimal voltage vectors and calculate their respective duration. Different from prior enumeration-based MPCC, this paper proposes an efficient two-vector MPCC by applying two arbitrary voltage vectors during one control period. The reference voltage vector is firstly calculated based on the principle of deadbeat current control. Two optimal vectors and their duration are then obtained in a very efficient way, which does not require the calculation of current slopes in prior MPCC methods. The proposed method is compared to the state-of-the-art predictive control methods, including conventional MPCC, MPCC with duty cycle control, deadbeat control with space vector modulation (SVM) and modulated model predictive control (M2PC). Both simulation and experimental results prove that the proposed method achieves better steady state performance than conventional MPCC with or without duty cycle and the dynamic response is not degraded. Under the condition of insufficient dc bus voltage, the proposed method outperforms deadbeat control and M2PC by presenting even higher speed range and less torque ripples.

Voltage source converters (VSCs) have been widely used due to their flexibility to control voltages and power independently and bi-directionally. Typically, the control system of VSCs mainly consists of two parts; outer voltage and power controllers and inner current controllers. The vector current control based dq decoupling technique enables to control the active power, reactive power, DC voltage and AC voltage. However, the d- and q-axis of grid voltages and currents comprise AC and DC components under unbalanced grid conditions. The AC components of the d- and q-axis currents make the grid currents unbalanced. In this paper, a novel current control is presented and investigated under unbalanced grid condition for a Back-to-Back Modular Multilevel Converter (B2B-MMC) based HVDC system and validated using the Real Time Digital Simulator (RTDS). Further, the active power oscillation under fault is eliminated by controlling the AC component of grid currents in the dq frame. The RTDS results demonstrate the feasibility of the proposed controllers under unbalanced grid voltage conditions.

In this paper, using the two control methods of model predictive control (MPC), model predictive current control (MPCC) and model predictive torque control (MPTC) is applied to the control system of permanent magnet synchronous motor(PMSM). The algorithms are based on the minimization of different cost functions, and the corresponding optimal voltage vector can be obtained. Comparison of the dynamic and steady state performance of the tested PMSM with MPCC and MPTC is elaborated. The delay compensation is considered to reduce the fluctuation of current and torque, in order to reduce the computational burden by using a single vector, comparison of two methods in the speed control system of dynamic and steady-state performance and speed tracking performance and resistance to load disturbance. The simulation results show that both MPCC and MPTC can be well applied to the PMSM driving systems with good speed tracking performance. However the MPCC can achieve less harmonics in the stator currents, and consequently the circular flux linkage trajectory is smoother, while the MPTC shows advantages in smaller ripples in the mechanical torque.

There are some problems in VIENNA rectifier under unbalanced grid voltage conditions, such as DC bus voltage fluctuation, active reactive power pulsation and serious harmonic distortion of grid side current. The model predictive control with fixed switching frequency(FCS-MPC) is proposed. The instruction voltage is obtained by double loop control of FCS-MPC and voltage outer loop control. The SVPWM modulation module is used to modulate the instruction voltage to generate the driving pulse signal of the VIENNA rectifier. Because the output polarity of SVPWM modulation of the VIENNA rectifier is different at each small sector pulse, the output pulse polarity configuration of the comparator in the PWM module needs to be changed continuously in one switching cycle, which can not be realized. The control method with DSP and FPGA is developed in this paper. The complex comparison part of SVPWM modulation is accomplished by FPGA. Finally, the experimental prototype of a 7.5KW three level VIENNA rectifier was built to verify the proposed control strategy. The experimental results have shown that the method is correct and effective under the condition of unbalanced voltage.

A novel control scheme for DFIG-based wind energy systems under unbalanced grid conditions

For the power control problem of a bidirectional voltage-source converter, because only one voltage vector is applied at each control period, the traditional model predictive direct power control strategy brings in high harmonic content. In this paper, a hybrid vector-modulation model predictive direct power control scheme is developed to address the high harmonic distortion issue under unbalanced grid conditions. Based on the instantaneous power theory, the expression for the power fluctuation is derived under unbalanced grid voltages. The new reference power under unbalanced grid voltages is represented by the α β components of the grid voltages and their orthogonal signals lagging by 9 0 ∘ . By means of the proposed strategy, neither the phase-locked loops nor the sequence extraction of the grid voltages are required. In addition, the optimal voltage vector is selected from eighteen alternative hybrid voltage vectors to further improve control performance. The effectiveness of the proposed strategy is verified through real-time simulations conducted on an RT-LAB hardware-in-the-loop platform.

Grid converters are the key player in renewable energy integration. The high penetration of renewable energy systems is calling for new more stringent grid requirements. As a consequence, the grid converters should be able to exhibit advanced functions like: dynamic control of active and reactive power, operation within a wide range of voltage and frequency, voltage ride-through capability, reactive current injection during faults, grid services support. This book explains the topologies, modulation and control of grid converters for both photovoltaic and wind power applications. In addition to power electronics, this book focuses on the specific applications in photovoltaic wind power systems where grid condition is an essential factor. With a review of the most recent grid requirements for photovoltaic and wind power systems, the book discusses these other relevant issues: Modern grid inverter topologies for photovoltaic and wind turbines Islanding detection methods for photovoltaic systems Synchronization techniques based on second order generalized integrators (SOGI) Advanced synchronization techniques with robust operation under grid unbalance condition grid filter design and active damping techniques Power control under grid fault conditions, considering both positive and negative sequences Grid Converters for Photovoltaic and Wind Power Systems is intended as a coursebook for graduated students with a background in electrical engineering and also for professionals in the evolving renewable energy industry.

The research object of this paper is single-phase PWM rectifier, the purpose is to reduce the total harmonic distortion (THD) of the grid-side current. A model predictive current control (MPCC) with fixed switching frequency and dead-time compensation is proposed. First, a combination of an effective vector and two zero vectors is used to fix the switching frequency, and a current prediction equation based on the effective vector’s optimal action time is derived. The optimal action time is resolved from the cost function. Furthermore, in order to perfect the established prediction model and suppress the current waveform distortion as a consequence of the dead-time effect, the dead-time’s influence on the switching vector’s action time is analyzed, and the current prediction equation is revised. According to the experimental results, the conclusion is that, firstly, compared with finite-control-set model predictive control, proportional-integral-based instantaneous current control (PI-ICC) scheme and model predictive direct power control (MP-DPC), the proposed MPCC has the lowest current THD. In addition, the proposed MPCC has a shorter execution time than MP-DPC and has fewer adjusted parameters than PI-ICC. In addition, the dead-time compensation scheme successfully suppresses the zero-current clamping effects, and reduce the current THD.

Traditional model predictive current control (MPCC) for motors can only choose one optimal voltage vector during one control period, which creates problems of over-regulation or under-regulation for the current tracking. With zero vectors being injected in the chosen optimal voltage vector, the traditional MPCC can obtain better performance, which is called duty cycle MPCC. However, whether the traditional or the duty cycle MPCC is being applied to multiphase motors, it is more difficult for the phase to increase. In this paper, a general double vector-based MPCC mechanism has been studied for a dual three-phase permanent synchronous motor (PMSM) with dual Y shift 30° windings used in aerospace propulsion. Firstly, the choosing range of the second voltage vector in duty cycle MPCC was extended to an arbitrary vector; then, the cost function was rationally designed, and the delay compensation was added to improve the control performance as well. Compared with the traditional or duty cycle MPCC, this general double vector-based MPCC has better torque performance and fewer total harmonic distortions in the full speed range and under different load conditions.

In this paper, a dual-converter three-phase pulse width modulation (PWM) rectifier based on unbalanced one-cycle control (OCC) strategy is proposed. The proposed rectifier is used to eliminate the second harmonic waves of DC voltage and distortion of line currents under unbalanced input grid voltage conditions. The dual-converter PWM rectifier employs two converters, which are called positive-sequence converter and negative-sequence converter. The unbalanced OCC system compensates feedback currents of positive-sequence converter via grid negative-sequence voltages, as well as compensates feedback currents of negative-sequence converter via grid positive-sequence voltages. The AC currents of positive- and negative-sequence converter are controlled to be symmetrical. Thus, the workload of every switching device of converter is balanced. Only one conventional PI controller is adopted to achieve invariant power control. Then, the parameter tuning is simplified, and the extraction for positive- and negative-sequence currents is not needed anymore. The effectiveness and the viability of the control strategy are demonstrated through detailed experimental verification.