Control Of Grid-connected Inverter Research Articles

Power Control Strategy for Grid-Connected Inverters in Stationary Reference Frame

The control of grid-connected converters in stationary reference frame has been investigated in several works of literature. One of the challenges of this method is in the computation of the current computing current references as a function of power references. In some works, this issue has been solved based on instantaneous power theory equations described in the stationary reference frame. However, this approach can lead to steady-state errors in the injected power if there is an error in the current control loop, which is the focus of this investigation. Firstly, analytical expressions are derived to investigate the effect of current loop steady-state error in the active and reactive power injected into the grid. Then, this paper proposes a closed-loop power control for grid-connected inverters controlled in the stationary reference frame. This strategy is experimentally investigated in two power conversion system configurations for battery energy storage systems. The results indicate that the proposed scheme guarantees zero steady-state error in the injected power even when the current loop presents an amplitude and phase steady-state error.

Nonlinear PID (N-PID) Controller for SSSP Grid Connected Inverter Control of Photovoltaic Systems

In this work, a Nonlinear Proportional Integral Derivative (N-PID) controller based on Popov's stability criterion is applied for retaining the power quality of single stage single phase grid connected photovoltaic systems. Popov's stability criterion based nonlinear gain is added with conventional PID controller design which is termed as N-PID. Here, Nonlinear gain is designed with the approach of the controller to provide a nonlinear relationship with the error for the accuracy in reference tracking as conventional PID controller shows a linear relationship with the error. Thus, the N-PID controller joins the benefits of conventional PID controller and also reduces the complexity of tuning of PID gains as tuning of PID gains is the most challenging process of the conventional PID controller to achieve the accuracy on set point tracking. N-PID is designed in such a way to control the duty cycle of DC-AC converter for obtaining the maximum power without any harmonics, also for achieving unity power factor and achieving the efficiency with 96%-99% of the system. The proposed topology with N-PID controller ensures fast tracking of maximum power point, reducing harmonics considerably and improving the efficiency further with the wide investigation of error over the responses.

Adaptive Current Control for Grid-Connected Inverter with Dynamic Recurrent Fuzzy-Neural-Network

The grid-connected inverter is a vital power electronic equipment connecting distributed generation (DG) systems to the utility grid. The quality of the grid-connected current is directly related to the safe and stable operation of the grid-connected system. This study successfully constructed a robust control system for a grid-connected inverter through a dynamic recurrent fuzzy-neural-network imitating sliding-mode control (DRFNNISMC) framework. Firstly, the dynamic model considering system uncertainties of the grid-connected inverter is described for the global integral sliding-mode control (GISMC) design. In order to overcome the chattering phenomena and the dependence of the dynamic information in the GISMC, a model-free dynamic recurrent fuzzy-neural-network (DRFNN) is proposed as a major controller to approximate the GISMC law without the extra compensator. In the DRFNN, a Petri net with varied threshold is incorporated to fire the rules, and only the parameters of the fired rules are adapted to alleviate the computational workload. Moreover, the network is designed with internal recurrent loops to improve the dynamic mapping capability considering the uncertainties in the control system. In addition, to assure the parameter convergence in the adaptation and the stability of the designed control system, the adaptation laws for the parameters of the DRFNN are deduced by the projection theorem and Lyapunov stability theory. Finally, the experimental comparisons with the GISMC scheme are performed in an inverter prototype to verify the superior performance of the proposed DRFNNISMC framework for the grid-connected current control.

An Inductance Online Identification-Based Model Predictive Control Method for Grid-Connected Inverters With an Improved Phase-Locked Loop

To simplify the tuning process and enhance the parameter robustness of the model predictive control (MPC) for grid-connected inverters, an improved phase-locked loop (PLL) and a new inductance online identification method are proposed in this article. First, an improved finite control set-based PLL is presented, which removes the PI controller, simplifying the tuning process. Next, a new inductance online identification method based on a model reference adaptive system is presented, which takes the actual grid voltage and the estimated one as the reference model and adjustable model, respectively. Here, a sliding mode observer (SMO) is proposed to estimate the grid voltage, and the inductance adaptive law is deduced by exploring the effects of the inductance on the estimated grid voltage. Furthermore, the sensitivity of the proposed SMO to frequency deviation is also analyzed, which shows that a proper sliding mode gain can be selected to reduce the effects of frequency deviation. Thus, a fixed grid frequency of 50 Hz can be used in the proposed SMO, indicating that it is not required to calculate the actual grid frequency using differential operation any more. Finally, experimental studies verify the validity of the proposed strategies.

Model Predictive Control Based Grid Connected Inverter for Renewable Energy Applications

Model Predictive Control (MPC) for grid-connected inverters has been presented in this paper. The standard proportional-integral controller based system is replaced by this control method for a two-level inverter using Euler's approximation technique to improve the inverter's dynamic response. To anticipate the grid-connected inverter's longer-term behaviour, a replacement predictive mathematical model is offered, which is likened to the reference signal to decide the system's cost function. With this MPC approach, the cost functions of the converter are derived using all possible switching vectors. The associated switching vector for the minimal possible function is then chosen to activate the inverter switches throughout the subsequent sampling instant. The suggested scheme is validated in Simulink to verify its effectiveness and performance. In comparison to the PI-based controller, total harmonic distortion (THD) and current error are minimized.

Reinforcement Q-Learning Based Current Control for Grid-Connected Three-Phase Inverters with Unknown System Dynamics

This paper proposes a Q-learning-based state feedback suboptimal controller to solve the current control problem of three-phase grid-connected LCL coupled inverters with unknown circuit parameters. In practice, the circuit parameters of the inverters will change obviously for reasons such as calculation errors, external environment and operation aging, which makes the dynamics of the inverter system become unknown. With the circuit’s model of the LCL inverters and the reference current dynamic, an augmented system is constructed and a discounted performance function is formulated as the optimal objective of current control which transform it into a H∞ tracking control. Using Q-learning algorithm with model-free characteristics, a current controller is proposed in which an iterative reinforcement learning (RL) algorithm is embedded. Simulations are presented to verify the valid of the proposed control scheme, where especially the results shows that it can keep excellent control performance under the condition of inverter parameter mutation and grid voltage distortion.

Current-Limiting Virtual Synchronous Control and Stability Analysis Considering DC-Link Dynamics Under Normal and Faulty Grid Conditions

An improved nonlinear virtual synchronous control for three-phase grid-connected inverters, that can maintain a reliable operation under both normal and faulty grid conditions, i.e. balanced grid voltage sags, is proposed. The proposed controller can ensure a desired RMS current limitation at all times, provide virtual inertia and damping via the DC-link voltage and AC system frequency coupling, and realize the desired real and reactive power regulation without requiring accurate knowledge of the system parameters. Opposed to the conventional methods that use saturated PI controllers with or without anti-windup techniques to limit the reference value of the inverter current, the proposed controller includes a nonlinear bounded integrator, which limits the actual value (instead of the reference) of the inverter RMS current and leads to a fast system recovery even after significant grid voltage sags. The closed-loop stability of entire system is rigorously proven using nonlinear singular perturbation theory. Moreover, analytic conditions for the controller parameter selection to guarantee the stability of entire inverter system with the DC-link dynamics are provided. To prove the effectiveness of proposed controller and its superior performance compared to the traditional approaches, extensive Matlab/Simulink-based simulations are performed, followed by Typhoon-HIL hardware-in-the loop implementation using a TI microcontroller.

Line Voltage Sensorless Control of Grid-Connected Inverters Using Multisampling

Multisampling control provides an attractive way to improve the dynamics and stability of high-power three-phase grid-connected inverters. Beyond the desired performance in current control, more information can be acquired through multisampling. However, such an assumption is rarely discussed in grid-connected inverters. In order to fill this gap, a line voltage sensorless control scheme is proposed for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LCL</i> -filtered inverters. In this article, a multisampling is performed on the inverter-side current, and the linear regression of the multisampled current during zero vectors of inverter-modulation voltage is employed to estimate the filter capacitor voltage. Consequently, the cost of line voltage sensors is reduced and the failure of line voltage sensors is prevented when using multisampling current control. Furthermore, to address start-up transients, the line voltage can still be estimated by temporarily locking the upper arms of the inverter, and dc-link voltage can be precharged to the target value at the same time. Experimental results validate the effectiveness of the method on a down-scale inverter.

LMI-Based Model Predictive Current Control for an LCL-Filtered Grid-Connected Inverter under Unexpected Grid and System Uncertainties

To guarantee a system stability and reliable operation of an inductor-capacitor-inductor (LCL)-filtered grid-connected inverter (GCI) under unexpected grid and system uncertainties, a linear matrix inequality (LMI)-based model predictive control (MPC) is presented in this paper. Even though the conventional MPC scheme is constructed by a simple concept, it is difficult to determine an optimized weighting matrix of the MPC cost function against parameter discrepancies. To overcome this problem, the MPC scheme is combined with LMI-based optimization. The system states are estimated by the LMI-based current-type observer in the stationary reference frame to implement the proposed scheme. Additionally, the MPC scheme is combined with the disturbance observer to eliminate offset error, which improves the reference tracking performance. In comparison with the other studies, the proposed control method ensures high robust control performance under grid voltage imbalance, parameter uncertainty, and frequency variation. In addition, the proposed approach achieves a robust active damping even for the grid impedance variation without the need of considering further damping method. The control design step is systematic and straightforward. Furthermore, unlike the conventional schemes, the proposed controller does not require an integral term and the 2nd harmonic compensation term to obtain a good reference tracking performance under grid imbalanced condition, which contributes to the reduction of the controller complexity by decreasing the order of the controller model. To verify the effectiveness of the proposed LMI-based MPC control scheme, the simulation and experiments are carried out by using prototype three-phase GCI. The comprehensive simulation and experimental results clearly demonstrate the robustness of the proposed current controller under various adverse test conditions with unexpected grid and system uncertainties.

Active Disturbance Rejection Control of Three-Phase LCL Grid-Connected Inverter under Unbalanced Grid Voltage

When the three-phase LCL grid-connected inverter operates under the condition of unbalanced grid voltage, the influence of the negative sequence component in the grid voltage will cause the grid-connected inverter system to produce active and reactive dual-frequency interference. This will cause the grid-side current to have many low-order harmonics, mainly the third harmonic, which does not conform the IEEE-Std. 929–2000 standard. In order to solve this problem, this paper designs a current auto-disturbance-rejection controller, which speeds up the tracking response speed of the system and reduces the harmonic content of the grid-side current under unbalanced conditions. At the same time, optimize the phase-locked loop structure and introduce a notch filter in the modulation link to eliminate the third low-frequency harmonic components and further improve the quality of the grid-side current waveform. Finally, the correctness of the control strategy suggested in this paper is verified by MATLAB/Simulink simulation.

Raspberry Pi Design and Hardware Implementation of Fuzzy-PI Controller for Three-Phase Grid-Connected Inverter

A photovoltaic system is one of the major sources of renewable energy. The grid-connected inverter controllers play an important role in the conversion and transmission of solar energy. Therefore, they must be improved to meet the demands for grid interconnection. This article introduces the design and hardware implementation of the intelligent fuzzy-PI controller of the inverter part of the grid-connected photovoltaic system. First, the paper discusses the design of the three-phase grid-connected fuzzy-PI controller. Next, the paper describes the implementation of a Matlab graphical user interface (GUI) to design any grid-connected inverter and size the photovoltaic systems. The code generation of the fuzzy-PI controller of the system is accomplished by using Matlab Simulink simulation software. The hardware components of the PV system are implemented experimentally. In the hardware implementation, a 70 W prototype is realized to test the functionality of the controller, such that one can develop a realistic controller without taking risks or falling into security concerns in the case of performing experiments on high-power systems. The prototype proves that the controller model can be directly transformed from Simulink to the control device. It also shows that the fuzzy-PI controller is working properly in the 70-watt prototype. The achieved performance parameters of the proposed fuzzy-PI controller are satisfactory. The proposed method to design and implement the fuzzy-PI controller does not require complicated programming, where a Matlab coder is proposed to transform the Simulink controller into C code that can be directly utilized as a software control program loaded in the microcontrollers embedded in the hardware of the controller. The main result is that the fuzzy-PI controller for the three-phase grid-connected systems can be implemented using low-cost reconfigurable microcontrollers.

Higher‐order sliding mode current controller for grid‐connected distributed energy resources with LCL$\mathrm{LCL}$ filters under unknown grid voltage conditions

The control of the current injected into the grid with lower harmonics is considered as one of the most important issues for the grid integration of distributed energy resources (DERs). The unbalances and harmonics in the grid voltage usually pollute the current injected into the grid due to the power electronic interfaces, for example, inverters. To address such problems, the present paper proposes a nonlinear higher order sliding mode controller (HOSMC) for grid-connected three-phase inverters with LCL $\mathrm{LCL}$ filters in order to control the current injected into grid and improve the power quality. The proposed current controller injects the desired current into the grid with lower values of total harmonic distortions (THDs) under any grid voltage condition as well as it reduces the harmonics in the grid voltage. Apart from these, the proposed scheme is developed to provide robustness against parametric uncertainties where these uncertainties are modeled using the Taylor series expansion method. Finally, the performance of the system is evaluated using processor-in-loop (PIL) simulations via MATLAB/Simulink platform through the implementation on a system considering the capacity of the DER as 2 kVA per phase and compared with other existing control strategies.

Immersion and invariance based active disturbance rejection control for LCL grid-connected inverter

To improve the anti-disturbance ability of LCL grid-connected inverter system, a novel immersion and invariance based on active disturbance rejection control(I&amp;I-ADRC) scheme is proposed in this paper. First, the target system with stronger anti-disturbance ability is immersed into the ADRC standard model by using the target system mapping method of immersion and invariance control. Then, the disturbance estimated by extended state observer (ESO) is compensated, and the immersion and invariance(I&amp;I) control law is adopted to design the state error feedback（SEF）control law, thus I&amp;I-ADRC is built, which has improved anti-disturbance ability and dynamic response performance. The stability of grid-connected inverter system is proved by Lyapunov theory. Simulation results show that the proposed strategy can effectively suppress the disturbance and has better tracking performance.

An Improved Three-Level Cascaded Control for LCL-Filtered Grid-Connected Inverter in Complex Grid Impedance Condition

The passivity-based control (PBC) with Euler&#x2013;Lagrange (EL) model has been used for LCL-filtered grid-connected converter. However, the impacts of the control delay and the interaction resonances under capacitive grid impedance are rarely considered for PBC method. Nonlinear Lyapunov&#x2019;s stability theory is hard to estimate the stability of the system and accurately design the controller parameters considering the control delay. This paper derived the impedance model of LCL-filtered grid-connected inverter with grid current control based on PBC method. The passive theory and the zero-pole maps are applied to reveal the influence of the digital delay and differential item of inverter current loop. A new three-level cascaded control method is then proposed based on traditional PBC method to achieve stability and high robustness in complex grid. Furthermore, controller parameters are designed accurately to maintain passivity within switching frequency ranges and parameter variations of the LCL filter are investigated. Final validation of the effectiveness and performance of the proposed control structure is performed by simulation and experimentation.

Repetitive Predictive Control for Current Control of Grid-Connected Inverter Under Distorted Voltage Conditions

A repetitive predictive control for grid-connected inverter current control scheme is presented in this paper under voltage harmonic distortion in the stationary reference frame. Predictive control is an approach that uses a receding horizon to achieve the optimal track for the reference. In this approach, the repetitive controller behavior is added to the predictive control to increase its performance under distorted voltage conditions. In addition, to apply the controller in the generation system, controller is designed from the perspectives of the power system. The controller is designed considering the state-space model in the stationary reference frame. The controller performance was verified using a laboratory experimental setup under distorted grid voltage condition. Experimental results confirm that the proposed controller can effectively suppress harmonics under both normal operation and distorted grid voltage conditions, and also satisfy the requirements stipulated in IEEE Std. 1547.2-2008.

A resonant damping control and analysis for LCL-type grid-connected inverter

The inverter becomes an essential part in the distributed energy units, where an inductor–capacitor–inductor (LCL) filter is an up-to-date adoption for grid interfacing. However, the challenging issue of resonance related to the LCL-filter worsens the dynamic control characteristics and produces stability threat for the voltage source inverter system. The proper design of inverter control plays a substantial part in ensuring a steady state operation and a high quality of grid injected current according to grid connection codes. This paper offers a different design method of inverter control which alters the inner damping loop structure to enhance the damping and stability features of the inverter system. In the proposed solution, a modified compensator is employed through the LCL filter network and filter capacitor current feedback loop, the resultant augmented plant’s output is then sent back at the reference point of a grid-connected inverter system to damp the unwanted resonance spike. This particular arrangement to form a damping loop is termed as parallel feedforward compensation. The damping loop is implemented by calculating the filter capacitor current, and a first order high-pass filter is employed as a damper in the suggested arrangement. Moreover, for comparative studies and analysis, the conventional filter capacitor current feedback active damping method is selected. In addition, the stability margins and control performance of the open current loop are examined under different filter parameters values. The substantial results of the suggested structure are quicker dynamic response, comparatively improved resonance damping, better tracking performance and higher delay compensation capability. A laboratory prototype is established to confirm the effectiveness of the suggested scheme on the bases of control performance and stability margins.

Impedance Adaptive Dual-Mode Control of Grid-Connected Inverters With Large Fluctuation of SCR and Its Stability Analysis Based on D-Partition Method

The stable operation of grid-connected inverters (GCIs) with traditional current source mode (CSM) control is affected by the large fluctuations of short-circuit ratio (SCR) under weak grids. Improved CSM control enhances the stability of GCIs under weak grids but remains unstable for very weak grids, while the stability of GCIs with voltage source mode (VSM) is just the opposite. Therefore, previous research works have proposed the impedance adaptive dual-mode control strategy: when the SCR is large, the GCI is controlled by CSM, and when the SCR is small, it is controlled by VSM. However, the existing literature still lacks the analysis of the parameter stability region and mode switching boundary of GCI in different modes. Therefore, based on the D-partition method, this article derives the parameter stability region of GCI in different modes under the constraints of multiple performance indexes such as phase and gain margin, current-loop bandwidth and phase-locked loop bandwidth, and the switching boundaries of CSM and VSM are also proposed. Finally, based on the grid impedance identification algorithm, the impedance adaptive dual-mode control is realized, which effectively improves the stability of GCI when SCR fluctuates greatly, and the experimental results verify the correctness of the above analysis.

A novel algorithm of MGWO-based PI controller for a single-stage grid-connected flyback inverter with ZVS

An effective approach on zero-voltage switching scheme for a single-stage grid-connected flyback inverter along with the introduction of Modified Grey Wolf Optimizer technique based on the proportional integral controller is proposed. A focus on soft-switching is attained by means of permitting the grid-side negative current along the bidirectional switches held in the transformer’s secondary side. Consequently, there is a discharge of metal–oxide–semiconductor field-effect transistor’s output capacitor. This function led the primary switch to turn ON at the condition of zero voltage. Therefore, it is essential to optimize the reactive current level for attaining zero-voltage switching. Generally, the basic Grey Wolf Optimization has some more disadvantages of accuracy-solving and less capability of finding the fitness solutions. Hence, to overcome this, optimizer can be modified for further enhancement in the optimization process. Modified Grey Wolf Optimizer based on the proportional integral controller with pulse width modulation technique is used for controlling the switches; thereby zero-voltage switching triggering takes place which results in decreased total harmonic distortion. Finally, the simulations can be carried out based on the total harmonic distortion which helps to illustrate the effectiveness of the suggested algorithm. A 24-V, 325-W prototype has been carried out to verify the proposed system.

Current PIλ Control of the Single-Phase Grid Inverter

In a grid-connected power generation system, the grid-connected current of the inverter is sensitive to nonlinear factors such as periodic disturbance of grid voltage, which results in grid-connected current waveform distortion. By establishing a single-phase photovoltaic grid-connected inverter control system model, designing an inverse current fractional-order PI (PIλ or FO-PI) controller and the dynamic and steady-state performance, antidisturbance and grid connection inversion characteristics of the system are simulated and compared under the action of the integer-order PI controller and fractional-order PI controller. The quality of the inverter grid-connected current is analyzed by using the fast Fourier transform (FFT). The simulation results show that the fractional-order control system can reduce the total harmonic distortion (THD) of the grid-connected current and dynamic performance and antidisturbance ability of the improving system while satisfying the steady-state performance indexes.

Three vector modulation model predictive control of grid-connected inverter

Aimed at the issues of the fixed range of vector selection, fixed amplitude, and fixed direction in the conventional single and double vector model predictive control for grid-connected inverters, such as the large current pulsation and poor steady-state performance of the system, a three-vector model predictive control strategy is proposed. Firstly, the desired voltage vector is equivalent to the combination of two adjacent non-zero voltage vectors and one zero voltage vector in a control period. Secondly, Choose the best vector combination by optimizing the objective function twice. The output optimal voltage vector combination is modulated to generate a PWM wave, which acts on the grid-connected inverter. Finally, the proposed three-vector model predictive control and the traditional single and double vector model predictive control are simulated and compared. From the simulation results, when the grid-connected reference current is 10 A, the harmonic current content of the grid-connected inverter is 2.98%, 2.48%, 1.13% under the single-vector, double-vector and three-vector model predictive control, respectively. combined with the results of the dynamic simulation experiments, the results show that under the three-vector control, the results show that the three-vector model predictive control grid-connected inverter enjoys less harmonic content, lower loss, more efficient operation, and stronger robustness.