Direct Power Control Strategy Research Articles

A whole control strategy for cascaded H‐bridge rectifiers under distorted grid voltage and unbalanced load

AbstractControl for single‐phase cascaded H‐bridge rectifier (CHBR) under distorted grid voltage is seldom discussed in the existing control methods; a modified direct power control (DPC) scheme is therefore proposed in this paper. A simple power control structure with proportional‐integral control method is first presented, which can discard phase‐locked loop (PLL) and coordinate transformation. Then, an improved fictitious orthogonal algorithm is proposed to provide a better anti‐disturbance ability compared with the traditional second‐order generalized integrator (SOGI). Since the orthogonal component of the grid current runs concurrently with the power reference, it offers an excellent dynamic performance in inner loop. On the other hand, a voltage balancing control (VBC) model by the relationship between the difference of dc‐side voltage square and that of power is established. On this basis, an internal model VBC (IM‐VBC) method is provided to reduce the parameter tuning complexity. With this method, the dynamic performance of voltage balancing on the dc side is improved. Finally, several test results on hardware‐in‐the‐loop (HIL) and scale‐down platform are demonstrated, which validate the effectiveness and superiority of the proposed control strategy.

Backstepping-Based Direct Power Control for Dual-Cage Rotor Brushless Doubly Fed Induction Generator

In this article, we propose a backstepping (BS)-based direct power control (DPC) strategy for the dual-cage rotor brushless doubly fed induction generator (DCR-BDFIG). The relationship between the power winding (PW) output power and the control winding (CW) voltage is derived according to the complete mathematical model of DCR-BDFIG. Based on that, a BS-based DPC controller, also known as a nonlinear controller, is designed with the global asymptotic stability analyzed for the grid-connected DCR-BDFIG. Compared with the dual-closed-loop control in the advanced vector control method, only single-closed-loop is required for the PW power in the proposed BS-based control scheme, and thus it has more simple structure and faster responses. The global stability of the proposed control scheme can be easily guaranteed with a Lyapunov function properly selected. In addition, in order to improve the performance of the proposed BS-based DPC strategy under unbalanced network, the resonant controller is introduced to suppress the oscillating components in the PW power, PW current, and CW current, whose harmonic order is twice of the grid frequency referring to the synchronous reference frame. Finally, the detailed experimental results demonstrate the effectiveness of the proposed control strategy.

Rooted Tree Optimization for Wind Turbine Optimum Control Based on Energy Storage System

The integration of wind turbines (WTs) in variable speed drive systems belongs to the main factors causing low stability in electrical networks. Therefore, in order to avoid this issue, WTs hybridization with a storage system is a mandatory. This paper investigates WT system operating at variable speed. The system contains of a permanent magnet synchronous generator (PMSG) supported by a battery storage system (BSS). To enhance the quality of active and reactive power injected into the network, direct power control (DPC) scheme utilizing space-vector modulation (SVM) technique based on proportional-integral (PI) control is proposed. Meanwhile, to improve the rendition of this method (DPC-SVM-PI), the rooted tree optimization technique (RTO) algorithm-based controller parameter identification is used to achieve PI optimal gains. To compare the performance of RTO-based controllers, they were implemented and tested along with some other popular controllers under different working conditions. The obtained results have shown the supremacy of the suggested PIRTO algorithm compared to competing controllers regarding total harmonic distortion (THD), overshoot percentage, settling time, rise time, average active power value, overall efficiency, and active power steady-state error.

Direct Power Control of a Surface-Mounted Permanent Magnet Synchronous Generator Wind Turbine for Offshore Applications

This paper proposes a direct power control scheme for an offshore wind turbine-driven surface-mounted permanent magnet synchronous generator with a full back-to-back converter situated onshore to decentralize the weight of the turbine. The proposed model is designed in a stationary reference frame and does not require a phase-locked loop as opposed to the traditional vector current control method. Simple feed-forward and feedback control loops are used in the proposed model to extract the maximum available wind power, maintain constant voltage at the coupling DC link, and ensure power injection into the electric network at unity power factor. Simulation results carried out in MATLAB/SIMULINK show that the proposed model has fast transient response and steady-state performance consistent with the vector current control model. Furthermore, eigenvalue analysis results demonstrate that the proposed method’s performance is robust to variations in different system parasitic elements, even under both stiff and weak electric network conditions. These results also indicate that the back-to-back converter can operate effectively when located onshore close to the load center, while the turbine is in close proximity offshore. This can be suitable for multiple specific offshore applications as it has the potential to reduce the overall weight, volume, and cost of the offshore wind turbine infrastructure.

Enhancement of Direct Power Control by Using Artificial Neural Network for a Doubly Fed Induction Generator-Based WECS: An Experimental Validation

Direct power control (DPC) is among the most popular control schemes used in renewable energy because of its many advantages such as simplicity, ease of execution, and speed of response compared to other controls. However, this method is characterized by defects and problems that limit its use, such as a large number of ripples at the levels of torque and active power, and a decrease in the quality of the power as a result of using the hysteresis controller to regulate the capacities. In this paper, a new idea of DPC using artificial neural networks (ANNs) is proposed to overcome these problems and defects, in which the proposed DPC of the doubly fed induction generators (DFIGs) is experimentally verified. ANN algorithms were used to compensate the hysteresis controller and switching table, whereby the results obtained from the proposed intelligent DPC technique are compared with both the classical DPC strategy and backstepping control. A comparison is made between the three proposed controls in terms of ripple ratio, durability, response time, current quality, and reference tracking, using several different tests. The experimental and simulation results extracted from dSPACE DS1104 Controller card Real-Time Interface (RTI) and Matlab/Simulink environment, respectively, have proven the robustness and the effectiveness of the designed intelligence DPC of the DFIG compared to traditional and backstepping controls in terms of the harmonic distortion of the stator current, dynamic response, precision, reference tracking ability, power ripples, robustness, overshoot, and stability.

Hybrid Data-Model Predictive Control for Enabling Participation of Renewables in Regulating Reserves Service

A long-horizon hybrid data-model predictive direct power control (HD-MPDPC) scheme is proposed. The hybrid control scheme is for grid-side power electronic converters (PEC) in grid-connected renewable energy sources (RES). Computational burden of conventional MPDPC is alleviated by reducing the number of candidate voltage vectors to be examined in the cost function. This is achieved by employing data-driven forecast of RES output power to identify and eliminate the voltage vectors that do not counteract active and reactive power errors appropriately. RES power is forecasted using recurrent neural networks. The method for eliminating voltage vector candidates is inspired from direct power control, where output of active and reactive power hysteresis controllers along with the sector in which grid voltage vector lies are used to determine the switching states of the grid-side PEC. Thanks to reduced computational complexity, the hybrid predictive control scheme dispatches RES power more reliably over long horizons. This in turn enables RES as a regulating reserves service provider in power systems. Hardware-in-the-loop studies of a grid-connected wave energy conversion system verify reduced computational complexity of HD-MPDPC and its effectiveness in controlling RES output power over long horizons.

Power Compensation-Oriented SVM-DPC Strategy for a Fault-Tolerant Back-to-Back Power Converter Based DFIM Shipboard Propulsion System

For safety critical transportation applications like all-electric ship propulsion systems (SPS), the reliable system operation is definitely the primary concern. In this paper, a fault-tolerant back-to-back power converter based on the four-switch three-phase (FSTP) topology is applied to a doubly-fed induction machine (DFIM) based all-electric SPS. A power compensation-oriented space vector modulation direct power control (PCSVM-DPC) strategy with dc-bus voltage unbalance elimination is proposed to ride through the single bridge arm open-circuit fault in the source-side converter (SSC) and improve the system dynamic performance simultaneously. Besides, the DFIM-SPS is endowed with excellent steady-state performance by applying the proposed control strategy. The dc-bus voltage deviation is suppressed based on the calculation of active and reactive power compensation terms to increase the dc-bus voltage utilization rate. Moreover, good post-fault system operation performance can be achieved with fast active power and electromagnetic torque tracking speeds. The proposed PCSVM-DPC strategy for the fault-tolerant FSTP SSC based DFIM-SPS is easy to implement without high computational burden. The SVM-DPC method is also presented for the load-side converter. The proposed control strategy is verified by experiments on a 1.5 kW DFIM-SPS experimental platform.

Comparative Study of BLDC Motor Drives with Different Approaches: FCS-Model Predictive Control and Hysteresis Current Control

The control techniques of the brushless DC (BLDC) motor have gained a large amount of interest in recent years, with their use being implemented in order to achieve a high-performance drive, including quick transient response and high-quality waveforms at the steady state. This paper provides a comparative study between three control schemes of BLDC motors: the direct power control scheme using a finite control set model predictive control (FCS-MPC) approach, the stator current controlled scheme using an FCS-MPC approach, and the stator current controlled scheme using ON–OFF hysteresis current controllers. The three systems were studied and investigated under the same operating conditions. The comparative study included investigating the performance of the BLDC drive in both steady state and transient operations. Qualitative and quantitative analyses were performed on the results obtained with each control scheme. The obtained results demonstrate the validity and effectiveness of the three investigated schemes in controlling the motor speed to the desired value under sudden load changes and achieving satisfactory quick transient responses. However, the results indicate the superiority of the direct power control scheme using an FCS-MPC approach over the others in terms of its minimum torque ripple, lowest torque and speed pulsations, minimum active and reactive power ripples, and high-quality waveforms of the stator currents drawn by the motor with minimum THD.

Efficient PMSG wind turbine with energy storage system control based shuffled complex evolution optimizer

To well manage the quality of the injected electrical power into the grid from a variable speed wind turbine (VSWT), direct power control (DPC) scheme using second order sliding mode control (SOSMC) based on super-twisting algorithm (STA) approach is proposed. Meanwhile, for reaching the adequate gains of STA, an appropriate optimizer should be implemented. Therefore, shuffled complex evolution (SCE) algorithm-based parameter identification is suggested. To verify the effectiveness of the proposed SCE based controller, several well-known algorithms have been tested under various operating conditions namely: particle swarm optimizer (PSO), artificial bee colony optimizer (ABCO), ant colony optimization (ACO), rooted tree optimizer (RTO) and gray wolf optimizer (GWO). The results confirm the superiority of the proposed SCE algorithm among the competing algorithms and classic SMC regarding the active power steady-state error (0.7233%), undershoot percentage (0.1333%), settling time (0.6810 × 10−3 s), rise time (1.7515 × 10−4 s), peak value (7.0521 × 103 W), overall efficiency (99.2800%), and total harmonic distortion (0.7900%). The proposed SCE based controller allows getting important performances under various operating condition of wind speed and load variations with interesting electrical network stability.

Direct Power Control Based on Modified Sliding Mode Controller for a Variable-Speed Multi-Rotor Wind Turbine System Using PWM Strategy

A robust and improved control scheme of a variable speed multi-rotor wind turbine (MRWT) system with a doubly fed asynchronous generator (DFAG) is displayed in this work. In order to improve the performances and effectiveness of the traditional direct power control (DPC) strategy of the DFAG, a new kind of sliding mode controller (SMC) called modified SMC (MSMC) is proposed. The most important advantage of the DPC-MSMC strategy is to reduce the power ripples and improve the quality of the currents provided to the grid. In addition, to control the rotor inverter, a pulse width modulation (PWM) technique is used. The proposed DPC-MSMC strategy was modeled and simulated using MATLAB/Simulink software. The simulation results showed that the ripples in stator currents, active and reactive powers and torque were considerably reduced for the proposed DPC-MSMC strategy compared to the traditional DPC. Additionally, the proposed DPC-MSMC method works excellently to reduce the total harmonic distortion (THD) of the stator current in the case of variable wind speed. On the other hand, a robustness test against parametric variations showed and confirmed the robustness of the proposed technique compared to the classical method.

Nonlinear Predictive Direct Power Control Based on Space Vector Modulation of 3-Phase 3-Level Solar PV Integrated Unified Power Quality Conditioner

This paper presents a hybrid feedback linearisation-based predictive direct power control strategies of the unified power quality conditioner (UPQC) combined with a photovoltaic generator (PVG) using space vector modulation technique for power quality enhancement. The PVG-UPQC is acting as a universal conditioner for power quality enhancement and renewable energy integration simultaneously, and it mitigates harmonics in both voltage and current caused by nonlinear loads in addition to reactive power compensation. The PVG-UPQC is made up of a dc bus powered by the photovoltaic generator that connects shunt and series active power filters. The shunt filter functions as a current source and compensates for current harmonics. The series filter compensates for voltage harmonics and fluctuations such voltage sag/swell by acting as a voltage source. In order to enhance the performances of PVG-UPQC, a hybrid control method based on FL -PDPC combined with a three-level SVM controller is proposed. The aims are to deliver compensation signals faster and more accurately under a variety of load conditions, as well as eliminate voltage and current harmonics while maintaining good dynamic response. The performance of the suggested control scheme is validated by extensive simulation results obtained by Matlab/Simulink for a sensitive nonlinear load. These results are compared with those obtained with a linear PI controller proves the superiority and effectiveness of FL-PDPC controller.

DPC of Cross-compensated Virtual Flux Double Switch Table

Aiming at the problems of large power ripple, high harmonic components and DC bias on the AC side of the three-phase voltage rectifier Direct Power Control (DPC), as well as the shortcomings of the voltage output of the DC side busbar, the direct power control method of the cross-compensated virtual flux double switch meter has been proposed. The virtual flux can realize the sensorless mode on the input side of the circuit to reduce the high harmonic, even if the first-order low-pass filter is used to replace the integration region, there is still some error. On this basis, the two filters are connected in parallel for virtual flux compensation, and then the voltage vector is selected according to the instantaneous power change, and the sector is re-divided with the voltage as the control vector, and two independent switching state tables are designed. The cross-compensated virtual flux double-switch meter DPC is simulated and compared with the traditional DPC waveform, and the experimental results show that the cross-compensated virtual flux double-switch meter DPC strategy can effectively reduce the proportion of harmonic content, control power fluctuations, improve DC bias, has fast tracking effect, stabilize output voltage, and control active and reactive power flexibly. The three-phase voltage rectifier circuit occupies an important position for the pre-rectifier part of the charging power supply of electric vehicles, and the rectifier circuit that can stabilize the output DC voltage cannot only extend its service life for the charging power supply, but also reduce harmonic pollution.

Model predictive direct power control strategy for leakage current suppression on a grid‐connected three‐level inverter

AbstractThe nonisolated grid‐connected photovoltaic inverter system suffers from the problem of leakage current. Therefore, a leakage current suppression control strategy based on the model predictive direct power control is proposed for the three‐level four‐leg grid‐connected inverter. At first, the system model is established to analyze the factors that affect the leakage current and the potential of the neutral point. Second, the first three legs, inverting part, use model predictive direct power control, and the fourth leg of the inverter is used to maintain a constant common‐mode voltage to achieve the suppression of the leakage current. The fourth leg is indirectly controlled by the switch state of the first three legs; thus, the number of optimization times is reduced. Finally, by simulation, the leakage current is compared and analyzed with the three‐level three‐leg inverter under conditions with different parasitic capacitance values. The results show that the proposed strategy suppresses the leakage current by more than 60% without affecting the neutral point potential and has a fast optimization speed.

Model predictive direct power control of three-level T-type inverter-fed doubly-fed induction generator for wind energy system

The paper proposes a simplified direct power control strategy of a doubly-fed induction generator fed by a three-level T-type inverter based on finite control set model predictive control. A mathematical model based on grid voltage orientation was employed to determine the predictive values of the stator flux, rotor current, and capacitor voltages for all feasible rotor-side inverter output voltages. The active and reactive powers were calculated by using the grid voltage and the rotor current. A cost function was applied to track the active and reactive powers, maintain the balance of capacitor voltages, and reduce the common-mode voltage. The best switching control input was chosen by minimizing the cost function and implemented to the inverter. Different operating conditions of wind turbine systems were studied with Matlab/Simulink environment. The simulation results validate the improved performance of the proposed method compared with the classical control in terms of transient response and steady-state conditions.

Model Predictive Direct Power Control for Virtual-Flux-Based VSR With Optimal Switching Sequence

Three-phase voltage-source rectifier (VSR) has been widely used in energy, industry and other fields in the past few years. Model predictive control with optimal switching sequence (OSS-MPC) has further reduced output current THD and ripples with a constant switching frequency, compared with the conventional model predictive control (MPC). However, in practical application, the AC side voltage is often in a distorted state, which causes a distorted AC side current and a dramatic increase of THD. To overcome the drawback mentioned before, based on the analysis of OSS-MPC and combined with virtual flux oriented direct power control strategy, a virtual-flux-based model predictive direct power control strategy with optimal switching sequence (VF-OSS-MPDPC) is proposed in this paper. This control strategy for VSR combines the advantages of virtual-flux, low-pass filtering characteristics and optimal switching sequence model predictive control, which has high prediction accuracy and the AC current THD are greatly reduced under distorted AC voltage. The proposed control strategy can realize a constant switching frequency in steady-state operation without a modulator, which reduces the complexity of control strategy and the difficulty of AC side filter design. The proposed VF-OSS-MPDPC is validated through simulation and experiment compared with OSS-MPC, which proves the correctness and effectiveness of the proposed control strategy.

An Improved Sliding Mode Direct Power Control Strategy Based on Reactive Power Compensation for Vienna Rectifier

Vienna rectifiers are widely used in electric vehicle charging systems, wind power generation systems and other fields due to their excellent high-voltage resistance, small size and high efficiency. Aiming at the problems of the Vienna rectifier’s long response time, low anti-disturbance ability, and current zero-crossing distortion, a new sliding mode direct power control strategy based on disturbance compensation is proposed. Firstly, a model considering the uncertainty is established, and the neural network is used to estimate and compensate the uncertain disturbance. Secondly, aiming at the slow approach speed and slow system convergence of traditional control methods, a new approaching law sliding mode direct power control strategy is designed. Aiming at the current zero-crossing distortion, the reason is analyzed and a compensation method is proposed. Finally, simulations and experiments show that the proposed method has no voltage overshoot and converges faster, effectively improving the problem of different phases of voltage and current. The rectifier operates at unit power, has better steady-state performance and stronger anti-load disturbance ability. The current total harmonic distortion is controlled below 2%, and the current quality is effectively improved.

Model predictive direct power control scheme for Vienna rectifier with constant switching frequency

Model predictive direct power control (MPDPC) has strong robustness and fast dynamic response, so it is widely applied in the control system of grid-connected converter. However, the traditional FCS-MPC bears with variable switching state, which will reduce the current tracking accuracy, accidentally produce current ripple and electromagnetic noise. Here, a double closed-loop control strategy with constant switching frequency based on optimal switching sequence synthesis of model predictive direct power control (MPDPC-CF) in the inner loop and SMC control in the outer loop is proposed for the non-linear system of Vienna rectifier. Firstly, the Vienna rectifier is modelled to obtain the predicted values of input power. Then, the given values of active power and reactive power are obtained through the outer loop. Three adjacent voltage vectors with the lowest cost function in the sector are selected to synthesize the optimal voltage vector, and the pulse time of the corresponding vector is calculated according to the cost function of the voltage vector. To verify the correctness of the theoretical analysis, the Vienna rectifier is taken as the research object, and the comparison with the traditional MPDPC shows that the proposed constant frequency model predictive control has good steadystate and dynamic performance.

New intelligent direct power control of DFIG-based wind conversion system by using machine learning under variations of all operating and compensation modes

Wind Turbine (WT)-based Doubly-Fed Induction Generator (DFIG) is a nonlinear system, in which the wind has variable behavior, and the local reactive power depends on the random demand of the AC grid; all these make conventional controls insufficient for an adequate power output. Thus, a new direct power control (DPC) strategy is proposed in this paper, to force the system to track the desired dynamics with higher performance and less drawbacks. This new approach is based on machine learning, Neural-Network- and Neuro-Fuzzy-DPC (NN- and NF-DPC), both are designed to overcome the problems related to power control, wind and local reactive power variations. All operating modes (sub-synchronous, super-synchronous and synchronous modes), with the possibility of local reactive power compensation are considered in this paper. Both NN and NF networks have been trained under the MATLAB interface. The trained NF showed better efficiency than the NN; the learning time is reduced to a few seconds with less computational effort, and less complexity. The effectiveness of both controls has been confirmed through simulation tests using MATLAB software. The obtained results have shown that the NF-DPC strategy presents better performances than NN-DPC and conventional control, with fast response, robustness, less power ripples and reduced Total Harmonic Distortion (THD) in the generated currents.

Research on Direct Power Control Strategy Based on Voltage Controlled Virtual Synchronous Generator

To support the “carbon peak and carbon neutrality” goal, new energy is poised to explode, and new energy power generation converter is simultaneously facing new challenges. The conventional current-controlled new energy converter can quickly transmit active power on the DC bus to the power grid. However, for the weak grid, the stability margin of the converter grid-connected system is reduced on the one hand, which can easily cause resonance oscillation; on the other hand, the current controlled converter cannot actively respond to system frequency and voltage fluctuation to offer support. The voltage controlled virtual synchronous generator (VVSG) is used to improve system small signal stability and frequency stability; however, its power response speed is too slow to meet the requirements of fast following power command. Although a voltage/current dual-mode switching control scheme is put forward to achieve characteristics complementary of current controlled converter and voltage-controlled converter, the control structure switching and intermediate variable following is required to realize mode switching, which is prone to large power shocks and switching failures. In view of the problem, a direct power control strategy based on VVSG is proposed. The control structure is raised based on a conventional VVSG outer active power control loop, and the output active power and frequency characteristics are analyzed. Compared with the voltage and current dual-mode control, VVSG with direct power control can perform large inertia characteristic in the weak grid and fast power following characteristics in the strong grid by adjusting λ, and without control structure switching and intermediate variable following. Moreover, the two characteristics can be smoothly transited. In addition, the active support ability of voltage source can be maintained under both characteristics. Finally, the effectiveness of the proposed control strategy is verified through simulation results.

An investigation of solar active power filter based on direct power control for voltage quality and energy transfer in grid-tied photovoltaic system under unbalanced and distorted conditions

This paper discusses a renewable energy system connected to a dual-function power grid through a shunt active power filter to improve the power quality and inject photovoltaic (PV) energy to the power grid in the presence of nonlinear loads. Disturbance rejection for this electrical network is provided by the proposed direct power control (DPC) command. The DPC strategy combines a fractional order PID controller for the regulation of the DC bus voltage with an intelligent method of tracking the maximum power point articulated on the fuzzy logic, reserved to address dynamic weather conditions. The quality of energy is offered by the improved DPC resides in the elimination of the undesirable harmonics of the source currents. Thus, the studied system operates under a power factor near unity with acceptable harmonic distortion, in agreement with the international standard IEEE-519. The overall control of the presented system is assessed under different states of the power source behavior—balanced, unbalanced, and distorted—through simulation using MATLAB/Simulink software. The results demonstrate the performance, robustness, and feasibility of the proposed methods compared to the existing techniques in the literature.