Hybrid Finite Control Set Model Predictive Control and Universal Droop Control for Enhanced Power Sharing in Inverter-Based Microgrids

Comparative Study of the Traditional, Arctan and Universal Droop Control Techniques for Proper Power Sharing in an Islanded Micro-Grid

In islanded operation, precise power sharing is an immensely critical challenge when there are different line impedance values among the different-rated inverters connected to the same electrical network. Issues in power sharing and voltage compensation at the point of common coupling, as well as the reverse circulating current between inverters, are problems in existing control strategies for parallel-connected inverters if mismatched line impedances are not addressed. Therefore, this study aims to develop an improved decentralized controller for good power sharing with voltage compensation using the predictive control scheme and circulating current minimization between the inverters’ current flow. The controller was developed based on adaptive virtual impedance (AVI) control, combined with finite control set–model predictive control (FCS-MPC). The AVI was used for the generation of reference voltage, which responded to the parameters from the virtual impedance loop control to be the input to the FCS-MPC for a faster tracking response and to have minimum tracking error for better pulse-width modulation generation in the space-vector form. As a result, the circulating current was maintained at below 5% and the inverters were able to share an equal power based on the load required. At the end, the performance of the AVI-based control scheme was compared with those of the conventional and static-virtual-impedance-based methods, which have also been tested in simulation using MATLAB/Simulink software 2021a version. The comparison results show that the AVI FCS MPC give 5% error compared to SVI at 10% and conventional PI at 20%, in which AVI is able to minimize the circulating current when mismatch impedance is applied to the DGs.

Numerous control techniques are being applied to control the parallel connected inverters. The well-known techniques among them are the communication and non-communication-based techniques. To avoid communication link, droop control technique is widely used in parallel connected inverter's based microgrids. Conventional droop control however in terms of power-frequency and reactive power-voltage do not attain desired outcomes for power sharing accuracy especially for reactive power sharing. Another problem in conventional droop control is the voltage deviations. This paper proposes a control technique which utilises the conventional and impedance power droop technique together. In this control technique impedance power droop control strategy is employed that individually has to deal with steady state conditions and conventional droop is used for start-up and transient states as a supplementary approach. Voltage deviation is totally removed as well as tracking errors at steady state are also decreased. Besides errors correction due to voltage deviation this technique does not need recognition of system parameters. Simulation results proves that proposed approach is very simple to implement with accurate power sharing capability.

In this paper, a Lyaupnov based finite control set model predictive direct torque control for the permanent magnet synchronous machine (PMSM) is proposed. In the proposed control scheme, the finite control set prediction and the Lyapunov theory are combined to minimize the torque ripple. The 8 voltage vectors of the 2-level converter are utilized as a finite control set for the torque prediction of the PMSM. A cost function considering the torque error, the Maximum Torque per Ampere (MTPA) operation and the current limitation is introduced. Comparing to the conventional finite control set predictive control, the dominant part of the cost function is utilized as a Lyapunov function to estimate the duty cycle of each voltage vector. An optimum voltage can be obtained by the optimum voltage vector from the 8 vectors and their duty cycles. A small sampling frequency and a fixed switching frequency can be realized when compared to the conventional finite set model predictive control. In the end, the simulation and experimental results validate the performance of the proposed control scheme.

This paper introduces the comparison of four predictive torque control schemes for a permanent-magnet synchronous machine (PMSM). The first method is the finite-set model predictive control (FS-MPC). In FS-MPC, the optimal switching state is selected based on the evaluation and minimization of a cost function for all possible voltage space vectors (VSVs) of the inverter. The second method performs a simplified FS-MPC where the selection and evaluation of the possible VSVs are reduced to only three. The third method is based on the principle of predictive direct torque control (PDTC), where the duty cycle of the switching state is optimized for application in the inverter. Finally, a method that combines FS-MPC and PDTC named model predictive torque control is presented. This paper introduces the methodology and the results of a comprehensive comparison of the four predictive schemes based on different criterions. The control schemes are implemented on a field-programmable gate array and are applied to a PMSM. Experimental results are presented to validate the presented comparison and discussion.

This paper focuses on the model predictive current control of power converters with the aim of indicating the influence of some system parameters used in predictive control on the load current and load voltage. A model predictive current control algorithm is proposed, specifically directed at the utilization of power obtained from renewable energy systems (RESs). In this study the renewable energy systems model is used to investigate system performance when power is supplied to a resistive-inductive load (RL-load). A finite set-model predictive current control (FS-MPCC) method is developed to control the output current of three-phase, voltage source inverter (VSI). The approximation methods for the derivatives of the model differential equations and delay compensation of model predictive control (MPC) system for power converters are assessed. Simulation results of a two-level, three-phase VSI using FS-MPCC are carried out to show the effects of different approximation methods on the load current and voltage regulation as well as on the predictive current control operation with and without delay compensation for different sampling times. It has been noticed that the ripple in the load currents is considerable when the delay compensation is not accounted for and the delay compensation method that reduces the ripple and operation is similar to the ideal case. It is confirmed that for larger sampling times the delay is noticeable, but when the sampling time is smaller it is not visible.

This paper proposes a finite set model predictive control (FS-MPC) based thrust maximization technique for linear induction machines used in linear metros. For modeling of the proposed control method, the end effect is taken into consideration. The proposed control method is used to achieve maximum thrust per ampere and to reduce the thrust ripples. It differs from the FS-MPC methods, where the cost function consists of the thrust and angle errors. The thrust error is calculated from the difference between the reference thrust and the predicted thrust, and the angle error is calculated from the difference between the angle of predicted primary current and the angle of the predicted secondary flux in one side and π /4 on the other side. A comparison between the proposed method and the finite set model predictive direct thrust control (FS-MPDTC) is presented to illustrate the superiority of the proposed method. Both simulation and experimental analysis are conducted to validate the effectiveness of the proposed finite set model predictive direct angle control (FS-MPDAC). A prototype test platform is developed in the laboratory with two 3 kW arc induction motors. The simulation model, experimental test platform, and test results are presented in this paper.

When GSC is connected to weak grid, the small signal instability can happen due to incompatible terminal characteristic of GSC and the grid impedance. Since higher disturbance rejection capability of GSC benefits the resolving of such stability problem, finite set model predictive control (FS-MPC) is applied. However, in weak grid, conventional FS-MPC shows poor performance as the total harmonic distortion (THD) of GSC output current is too high. To solve the problem, Kalman filter (KF) is used. The filtered signals are fed into the predictive controller instead of the directly measured current and voltage, which significantly reduce the harmonic distortion of GSC output current in the middle frequency range around 300~600Hz. Besides, in order to reduce the THD of output current, a three-level neutral point clamped (3L-NPC) grid side converter (GSC) is used. A simple sequential finite set prediction is applied to reduce the computational burden. The performance of proposed strategy is verified by simulation. Moreover, the impedance characteristic of the proposed MPC controller is presented, which is obtained by the perturbation test. From impedance viewpoint, the stability performance of proposed method in weak grid is analyzed, which is found promising.

Microgrid comprises of several distributed generations (DGs), which are typically integrated through power electronic inverters. The existence of low inertial devices combined with the dynamic nature of the load challenges the stability of a microgrid and the effectiveness of the controller, mainly when operated in islanded mode. It is essential to optimize the parameters of the controller to enhance its efficacy under various operating conditions. In this paper, parameter optimization of universal droop and internal model control (IMC) is proposed based on an accurate small-signal model for an inverter dominated microgrid. In order to achieve robust control performance under different load conditions, a four-step approach is proposed: 1) an accurate small-signal model of a parallel multi-inverter system is prepared, which operates with the universal droop and internal model controller. The developed small-signal model is more accurate because it considers the dynamics of filter and phase-locked loop; 2) an investigation of critical control parameters of universal droop and internal model controller influencing the system stability is carried out, and their corresponding stability domain is identified through eigenvalue analysis; 3) particle swarm optimization (PSO) is used to optimize the critical parameters; and 4) the obtained result is validated under different load disturbances. Following the above approach, the time domain simulation is performed, which establishes that the proposed scheme improves the dynamic response of the DGs, counteracts the disturbances effectively and simultaneously improves the power-sharing. The proposed model is also compared with the well-established conventional PI-based droop controller, which demonstrates the efficacy of the proposed scheme.

Frequency performance analysis of multi-gain droop controlled DFIG in an isolated microgrid using real-time digital simulator

This work introduces the control concept of variable sampling time finite control-set model predictive control (FCS-MPC). The new control concept is introduced in theory based on a review of the conventional FCS-MPC concepts performed with a constant sampling time. Based on the partitioning of the sampling instant in multiple smaller sampling instants it is possible to optimize, besides the switching states, the switching states turn-on times. Therefore, the proposed variable sampling time FCS-MPC sets both: the switching state and the related turn-on times. To utilize the available calculation power for longer sampling instants an adaptation of the control- and prediction horizon to the sampling time is proposed. The theoretical control concepts are applied to the control of a grid connected two-level voltage-source converter where a simple L-type line-filter is used to demonstrate the control performance of the variable sampling time FCS-MPC algorithms in the laboratory environment.

In this paper, a Lyaupnov-based finite control set model predictive direct torque control for the permanent magnet synchronous machine (PMSM) is proposed. In the proposed control scheme, the finite control set prediction and the Lyapunov theory are combined to minimize the torque ripple. The eight voltage vectors of the two-level converter are utilized as a finite control set for the torque prediction of the PMSM. A cost function considering the torque error, the maximum torque per ampere operation and the current limitation is introduced. Comparing to the conventional finite control set predictive control, the dominant part of the cost function is utilized as a Lyapunov function to estimate the duty cycle of each voltage vector. An optimum voltage can be obtained by the optimum voltage vector from the eight vectors and their duty cycles. A small sampling frequency and a fixed switching frequency can be realized when compared to the conventional finite set model predictive control. In the end, the simulation and experimental results validate the performance of the proposed control scheme.

Techno-enviro-socio-economic design and finite set model predictive current control of a grid-connected large-scale hybrid solar/wind energy system: A case study of Sokhna Industrial Zone, Egypt

To address inaccurate power sharing problems in autonomous islanding microgrids, an enhanced droop control method through online virtual impedance adjustment is proposed. First, a term associated with DG reactive power, imbalance power, or harmonic power is added to the conventional real power-frequency droop control. The transient real power variations caused by this term are captured to realize DG series virtual impedance tuning. With the regulation of DG virtual impedance at fundamental positive sequence, fundamental negative sequence, and harmonic frequencies, an accurate power sharing can be realized at the steady state. In order to activate the compensation scheme in multiple DG units in a synchronized manner, a low-bandwidth communication bus is adopted to send the compensation command from a microgrid central controller to DG unit local controllers, without involving any information from DG unit local controllers. The feasibility of the proposed method is verified by simulated and experimental results from a low-power three-phase microgrid prototype.

ABSTRACTThis paper introduces an innovative method for enhanced power distribution in an AC microgrid (MG), utilizing parallel inverters with a decentralized droop control strategy. The conventional droop (P‐f/Q‐V) control is implemented for inductive‐dominant lines and the reverse droop (P‐V/Q‐f) control for resistive‐dominant lines. However, since line impedance often includes both inductive and resistive components, a combined droop approach (P‐f/Q‐V and P‐V/Q‐f) is considered. Challenges like frequency and voltage deviations, improper power sharing, and instability at the point of common coupling arise from line impedance mismatches in systems with multiple distributed generators (DGs) operating in parallel. To address these, the paper proposes adding a virtual impedance loop to the existing control scheme. Two case studies are analyzed: The first examines the combined droop approach for two DGs, while the second evaluates the existing control scheme along with improved virtual impedance control for mismatched line impedance scenario. The MG model is validated using the OPAL‐RT OP 4510 digital simulator, with system modeling performed in the MATLAB/Simulink environment. The simulation results demonstrate improvements in stability of voltage, restoration of frequency, current, and power sharing accuracy for all case studies. A comparative analysis further highlights the percentage improvement in power sharing during transient conditions.