Controlled Voltage Source Inverter Research Articles

New droop-based control of parallel voltage source inverters in isolated microgrid

New droop-based control of parallel voltage source inverters in isolated microgrid

High-Frequency Modified Bridgeless AC-DC PFC Rectifier for Ceiling-Fan

High current percentage total harmonics distortion (%THD), low supply power factor (SPF), and high input-power are main concern in an existing brushless direct current motor ceiling-fan (BLDCMCF). This paper presents AC-DC coupled-inductor-based bridgeless switched-inductor Cuk-converter (CIB-BLSICC) for BLDCMCF to address these concerns. CIB-BLSICC improves supply power quality (SPQ) and reduces input-power. Switched-inductor branch using coupled-inductor provides high-step-down-gain (HSDG), which offers an appropriate operating duty for BLSICC. Front-end CIB-BLSICC is developed in discontinuous mode (DCM) with changeable output voltage and a low component count, which reduces converter's overall size. DCM design offers auto power-factor correction (PFC) at a supply-mains. Variable output-voltage makes voltage source inverter (VSI) control easy (offers inverter switching at fundamental-frequency) with low switching-losses and helps speed-control. In addition to improving CF's (ceiling-fan's) overall efficiency, bridgeless design of PFC-converter lowers losses caused by conduction. Using reference speed of fan, CIB-BLSICC calculates its operational duty in order to create fixed-frequency PWM-pulses (200 kHz) while supply-voltage remains constant. This simple-control brings CF's price down by removing need for a sophisticated sensing-circuit, a DC-link sensor, and a voltage-controller. Test results confirm concept and design, which demonstrate a %THD of 1.483%, a crest-factor of 1.48, SPF of 0.9991, and a power-input of 27.93 W.

Fuzzy logic based improved direct torque control of DFIG-based wind turbines

This paper investigates direct torque control with a fuzzy controller (F-DTC) for a two-level voltage source inverter feeding the rotor of a doubly-fed induction generator (DFIG) based on a variable-speed wind energy conversion system (VSWECS). The wind turbine's MPPT technology is used to obtain the torque reference. The proposed fuzzy logic-based direct torque control (F-DTC) is designed to eliminate the flux and electromagnetic torque ripples that are common with existing (DTC) controls, leading to smoother operation and improved efficiency in the wind energy conversion system. The fuzzy logic controller improves switching decision-making by handling uncertainties and non-linearities, resulting in smoother and more efficient control of the torque and flux. To validate the effectiveness of the proposed F-DTC method, simulations are conducted in MATLAB/SIMULINK, and the results are compared with those of the classical DTC approach. The findings demonstrate that the F-DTC strategy significantly reduces torque and flux ripples, enhances the dynamic response, and improves overall system performance.

The Influence of Switching Frequency on Control in Voltage Source Inverters

This paper aims to show how the switching frequency influences the properties of the digitally controlled voltage source inverter (VSI). The measurements of the Bode plots of the inverter are shown and discussed to present the existing signal delays and power conversion efficiency, depending on the switching/sampling frequency. Two types of controllers are presented, Single-Input–Single-Output (SISO) and Multi-Input–Single-Output (MISO), and adequate prediction units (the Smith Predictor for SISO—Coefficient Diagram Method and the full-state Luenberger Observer for MISO—Passivity Based Control) were used to compensate for the delays. It will be shown by comparing the THD of the VSI output voltage that prediction is useful with low VSI switching frequency (about 10 kHz) but is not important for the middle switching frequencies (about 25 kHz) or the high switching frequency (>50 kHz). This paper shows that increasing the switching frequency simplifies digital control without reasonably decreasing efficiency. The theoretical considerations, the Matlab/Simulink 2021b simulations, the final experimental laboratory verification are presented.

Decentralized Retrofit Model Predictive Control of Inverter-Interfaced Small-Scale Microgrids

In recent years, small-scale microgrids have become popular in the power system industry because they provide an efficient electrical power generation platform to guarantee autonomy and independence from the power grid, which is a critical feature in cases of catastrophic events or remote areas. On the other hand, due to the short distances among multiple distribution generation systems in small-scale microgrids, the interconnection couplings among them increase significantly, which jeopardizes the stability of the entire system. Therefore, this work proposes a novel method to design decentralized robust controllers based on a retrofit model predictive control scheme to tackle the issue of instability due to the short distances among generation systems. In this approach, the retrofit model predictive controller receives the measured feedback signal from the interconnection current and generates a control command signal to limit the interconnection current to prevent instability. To design a retrofit controller, only the model of a robust closed-loop system, as well as an interconnection line, is required. The model predictive control signal is added in parallel to the control signal from the existing robust voltage source inverter controller. Simulation results demonstrate the superior performance of the proposed technique as compared with the virtual impedance and retrofit linear quadratic regulator techniques (benchmarks) with respect to peak-load demand, plug-and-play capability, nonlinear load, and inverter efficiency.

Enhancing of single-stage grid-connected photovoltaic system using fuzzy logic controller

The power generated by photovoltaic (PV) systems is influenced by environmental factors. This variability hampers the control and utilization of solar cells' peak output. In this study, a single-stage grid-connected PV system is designed to enhance power quality. Our approach employs fuzzy logic in the direct power control (DPC) of a three-phase voltage source inverter (VSI), enabling seamless integration of the PV connected to the grid. Additionally, a fuzzy logic-based maximum power point tracking (MPPT) controller is adopted, which outperforms traditional methods like incremental conductance (INC) in enhancing solar cell efficiency and minimizing the response time. Moreover, the inverter's real-time active and reactive power is directly managed to achieve a unity power factor (UPF). The system's performance is assessed through MATLAB/Simulink implementation, showing marked improvement over conventional methods, particularly in steady-state and varying weather conditions. For solar irradiances of 500 and 1,000 W/m<sup>2</sup>, the results show that the proposed method reduces the total harmonic distortion (THD) of the injected current to the grid by approximately 46% and 38% compared to conventional methods, respectively. Furthermore, we compare the simulation results with IEEE standards to evaluate the system's grid compatibility.

Principle, Design, and Analysis of a Novel Discrete Pulse Control for Single-Phase Voltage Source Inverter

Principle, Design, and Analysis of a Novel Discrete Pulse Control for Single-Phase Voltage Source Inverter

Model-Free Predictive Current Controller for Voltage Source Inverters Using ARX Model and Recursive Least Squares

Model-Free Predictive Current Controller for Voltage Source Inverters Using ARX Model and Recursive Least Squares

Grid Tied Electric Vehicle Charging Station by Bidirectional PV Based High Gain Integrated DC-DC Converter

In the escalating concerns over carbon emissions from traditional fossil fuel vehicles, which contribute significantly to environmental degradation through phenomena like global warming and climate change, electric vehicles (EVs) have emerged as a compelling solution due to their emission free nature. This paper proposes the establishment of a grid connected electric vehicle charging station, powered by a cutting edge bidirectional PV based high-gain integrated DC-DC Cuk Landsman converter which shows 93.4 % efficiency, aimed at ensuring swift and efficient EV charging processes. To enhance dynamic performance, a Cascaded Fuzzy Controller (CFC) technique is implemented which shows 89.4 % accuracy. This technique enables rapid responses for error compensation, thereby improving the converter’s dynamic performance indices. The converter plays a pivotal role by adeptly converting the low and unregulated DC voltage generated by the PV system into a stable output at the requisite voltage level, all while attaining unity power factor and minimizing total harmonic distortion (THD). Grid synchronization is meticulously ensured through the implementation of an adaptive proportional integral (PI) controller for a single phase voltage source inverter (VSI), which meticulously compares reference power with actual power. This process ensures seamless integration with the grid, meeting stringent standards. Furthermore, an LC filter is deployed to effectively mitigate current harmonics around the switching frequency, ensuring compliance with grid regulations.

A new approach to MPPT hybrid incremental conductance-sliding mode control for PV grid-connected

As photovoltaic energy is clean, renewable, and less noisy, it is increasingly integrated into the grid. This integration aims to overcome energy deficits and get rid of pollution from conventional sources. In this paper, a two-stage configuration of PV energy conversion to a three-phase grid has been studied. The control of this configuration can be divided into two parts, such as DC bus control and AC bus control. The DC bus is controlled by MPPT control. The AC bus is controlled by DC link voltage control, phase-looked loop control, and voltage source inverter control. The contribution in this study aims to improve the quality of energy injected via a new hybrid approach to MPPT control. The proposed control is a combination of robust sliding-mode control and incremental inductance. Unlike conventional hybridization, the proposed control estimates correct the error upon entry of the conductance incremental control. This correction provides an adaptive incremental step for increment conductance control. The proposed control is compared with three other controls under MATLAB/Simulink. Such as incremental conductance, variable step size incremental conductance, and conventional hybrid MPPT incremental inductance-sliding mode control. The simulation results show a remarkable minimization of the ripple phenomenon and the chatter phenomenon. Thus, the quality of the energy injected into the network is improved, such as by reducing the total harmonic distortion of the current and increasing efficiency.

Non-linear control for enhanced solar power under partial shading and AC load variations

This paper solves the control problem to track the maximum power in grid-connected PV systems to catch up with the changes and meet the energy demand, given the irregular and arbitrary nature of the solar source. Our work addresses the following objectives: i) extracting the maximum available power under partial shading, ii) and having a unit power factor. To achieve the above objectives, we have integrated two control components. The first one is dedicated to the extraction of the maximum power point (MPPT) particle swarming algorithm (PSO) with a backstepping controller, by shaking on the DC/DC converter duty cycle to increase the robustness and stability of the system. The backstepping control of the three-phase voltage source inverter is the second part. To verify the effectiveness of the introduced system, modelling and simulation are verified in MATLAB/Simulink.

Power Quality Control of Micro Hydro Power Plant Based-ELC and VSI Using Fuzzy-PI Controller

Stability of frequency and voltage of micro hydro power plant (MHPP) are influenced by sufficiency of active power and reactive power respectively in handling load power. These powers are normally controlled by Electronic Load Controller (ELC) and Voltage Source Inverter (VSI), respectively. VSI is specifically added to compensate reactive power caused by inductive load. The objective of the study is to control active power and reactive power in MHPP system against the changes in load power through the improvement of ELC and VSI output responses by applying Fuzzy-PI controller. ELC applied Fuzzy-PI controller to obtain more precise TRIAC ignition angle to meet a suitable active power to balance the load power. While VSI implemented Fuzzy-PI controller to meet a precise reactive power needed to oppose inductive load power. Capability of Fuzzy-PI controller in improving ELC and VSI performance were assessed by using Matlab in complete MHPP model. Assessments on the proposed controller indicate that it was effective in improving the performance of both ELC and VSI. By applying Fuzzy-PI controller on ELC, a precise ignition angle of TRIAC stimulated a more precise ballast load to balance active power against the load power. While the addition of Fuzzy-PI controller on VSI produced more suitable reactive power to compensate for the inductive load presence. With a more stable frequency and voltage against changes in load power, the power quality of the MHPP also improve.

Experimental test performance for a comparative evaluation of a voltage source inverter: Dual voltage source inverter

Abstract This article proposes an adaptive Kernel-Hebbian least mean square (KHLMS) controller for a dual voltage source inverter (VSI). The recommended topology consists of a distributed energy resource (DER) supported VSI called main VSI (MVSI) and split capacitor supported VSI termed as auxiliary VSI (AVSI). Both the MVSI and AVSI are used to serve the shunt compensation when DER is not integrated with MVSI. The DER scenario is considered to suppress the active power flow shortage in the utility grid. Here, optimal active power flow control (OAPFC) is managed by MVSI and shunt compensation is achieved by AVSI during DER operated mode. Hence, a dual VSI based distribution static compensator (DSTATCOM) facilitates the configuration merits such as reduction in system downtime cost, filter rating switching stress etc. Supremacy of both the neural network (NN) based controller and topology is presented by comparing VSI (called AVSI) in the context of harmonic reduction in source side, voltage balancing, power factor (PF) enhancement, better voltage regulation and OAPFC. The experimental results are obtained through field programmable gate array (FPGA) based hardware units which exhibit radical improvement in the power quality (PQ) conferring as per the international standard grid code (IEEE-519-2017).

Voltage and Current Control Strategy for Grid Connected WECS Employing Two and Three Level Voltage Source Converters

This paper presents voltage and current control strategy for grid connected variable speed wind turbine induction generator employing two and three level voltage source inverters. Induction generators are widely used because of its low cost, robust construction and capability of feeding active power to load without getting reactive power from separate source. The mechanical energy required to drive the generator is obtained from a variable speed wind turbine. Three phase induction machine is excited from a three phase voltage source converter. The DC voltage of the capacitor is inverted and fed to the three phase grid using a current controlled voltage source inverter. Control strategy has been developed for maintaining the DC link voltage constant and also to feed the power at unity power factor to the grid, even though there is variation in wind speed. It is also shown that the harmonics are considerably reduced when a two level inverter is replaced by a three level inverter. The simulation study has been carried out using MATLAB/Simulink. Simulation results indicate the feasibility of control strategy.

Modelling, control design, and analysis of the inner control's loops intended for single‐phase voltage‐controlled inverter‐based microgrid

AbstractIn voltage‐controlled voltage source inverters (VSIs)‐based microgrids (MGs), the inner control is of prime interest task for guaranteeing safe and stable operation. In this paper, an in‐depth investigation of the modelling, control design, and analysis of the voltage and current inner control loops intended for single‐phase voltage‐controlled VSIs is established. The main objective of this work is to provide a comprehensive study of the mathematical modelling, control design, and performance evaluation of the inner control's loops considering different proportional‐integral (PI) controller types with and without compensation, and to determine the optimal scheme that can offer better performance in terms of implementation simplicity, robustness, and transient and steady‐state responses. Thus, the mathematical closed‐loop models of designed outer voltage and inner current control schemes based on PI, P, and feedforward controllers with and without compensation are, first, derived. Following this, a systematic and effective control design for tuning the different PI controllers’ parameters is proposed. Furthermore, an analysis revealing the performance of the designed voltage and current control schemes is provided. This analysis enables us to choose a P controller and PI feedforward controller for the current control loop and the voltage control loop, respectively. The chosen P and PI controllers should be simple; meanwhile, they should offer a wide bandwidth. A simulation study is carried out in MATLAB/Simulink software to assess the performance of the adopted inner control scheme for both linear and non‐linear loads. In addition, an experimental setup, based on a TMS320F2837xD μC, of a single‐phase VSI supplying linear and non‐linear loads is built to verify the effectiveness and the robustness of the adopted inner controller. The results demonstrated: (1) the necessity of introducing the compensation term, which is responsible for offering control improvement against voltage perturbation, (2) the high tracking performance of the chosen controller in terms of dynamic and steady‐state responses as well as its simplicity of implementation.

An Improved Mutated Predictive Control for Two-Level Voltage Source Inverter With Reduced Switching Losses

An Improved Mutated Predictive Control for Two-Level Voltage Source Inverter With Reduced Switching Losses

Current sensorless model predictive control for LC-filtered voltage source inverters based on sliding mode observer

Abstract In recent years, model predictive control (MPC) has gained significant traction within the realm of LC-filtered voltage source inverters (VSIs). In order to reduce the number of current sensors in conventional MPC, this paper proposes a MPC scheme without current sensors for LC-filtered VSIs. Firstly, this paper analyzes the mathematical model of LC-filtered VSIs and specifies the predictive control strategy based on capacitive current. On the basis of considering only the fundamental wave components of the capacitance current, this paper establishes a new sliding mode observer to observe the capacitance current. In order to ensure the stability of the system, the stability of the proposed sliding mode observer is analyzed using Lyapunov stability criterion, and the influence of the sliding mode gain on the current and voltage observations is also analyzed according to the closed-loop transfer function, giving the design method of the sliding mode gain. In addition, the parameter sensitivities of the newly proposed method and the conventional method are analyzed in detail in this paper. The results show that the method proposed in this paper does not depend on the filter inductance and the observed capacitance current have smaller errors and stronger parameter robustness than the conventional method. The comparative experimental study verifies the feasibility of the control scheme proposed in this paper.

Discrete space vector modulation and optimized switching sequence model predictive control for three-level voltage source inverters

This paper proposes a discrete space vector modulation and optimized switching sequence model predictive controller for three-level neutral-point-clamped inverters in grid-connected applications. The proposed strategy is based on cascaded model predictive control (MPC) for controlling the grid current while maintaining the capacitor voltage balanced without weighting factor. To enhance the closed-loop performance, the external MPC evaluates 19 basic and 138 virtual vectors (VV) of the proposed space vector method. The optimal control voltage is then selected using an extended deadbeat method to reduce the execution time of the proposed control algorithm. By using the discrete space vector modulation principle, the VV are synthesized based on switching sequence (SS) and are divided into negative and positive SSs considering their impact on the neutral point (NP) potential. The inner MPC evaluates both types of SSs and selects the one that keeps the capacitor voltage balanced. Various controllers are evaluated and compared against the proposed control strategy. The results show that the proposed strategy improves performance without weighting factor, while maintaining a total harmonic distortion of current to be less than 2%. Compared to the modulated MPC which provides the same fixed switching frequency, the proposed controller reduces the computational burden by over 50% while also providing better NP voltage balance accuracy.

Adaptive optimal sliding mode control for three-phase voltage source inverter: Reinforcement learning approach

The operation of the three-phase standalone inverter is affected by many factors, such as heavy changes in load, unbalanced loads, nonlinear loads, system uncertainties and external disturbances. These are critical weaknesses for the control system of the three-phase inverter to reach robust optimal performance. This paper proposes an adaptive optimal sliding mode control (AOSMC) scheme for a three-phase nonlinear uncertain inverter. This AOSMC strategy solves the problems of nonlinear optimization by adaptive dynamic programming, one of the techniques of reinforcement learning, and overcomes the uncertainties and disturbance effects by a disturbance observer–based sliding mode controller. This algorithm uses only one neural network to approximate the critic; therefore, the burden of computation is significantly reduced. Both the weight matrix of the critic network and the disturbance observer are asymptotically stable. The overall system is guaranteed to be ultimately uniformly bounded stable via Lyapunov stable theory. The simulation is conducted to validate the insensitivity of the proposed AOSMC algorithm to working conditions. Also, the competitive results are presented to demonstrate the improvement of the proposed AOSMC scheme in comparison to some other existing controllers.

Enhancing the Performance and Efficiency of Two-Level Voltage Source Inverters: A Modified Model Predictive Control Approach for Common-Mode Voltage Suppression

In this paper, a new modified model predictive control is proposed to improve the performance of the model predictive control for two-level voltage source inverters by alleviating computational burden and the disadvantages associated with the conventional model predictive control strategy. The objective of the proposed method is to reduce the number of candidate voltage vectors in each sector, thereby improving the overall performance of the control system, as well as achieving common-mode voltage reduction for two-level voltage source inverters. Two strategies are introduced to achieve this objective. Firstly, an algorithm is developed based on statistical computational processes to pre-define the candidate voltage vectors. This strategy involves ranking and considering the most frequently used voltage vectors. Consequently, by reducing the computational burden, the search space for the optimal voltage vectors is reduced. Furthermore, based on statistical results, a strategy is proposed to divide the sectors into three sectors instead of the six sectors in the conventional method. This approach effectively reduces the number of candidate voltage vectors. The modified model predictive control strategy aims to improve the efficiency of the control system by reducing the computational burden, and suppressing the common-mode voltage. The simulation and experiments are carried out to verify the effectiveness of the proposed strategy under various operational conditions. The results demonstrate that the modified model predictive control approach significantly reduces the computational burden and complexity of the control system while effectively suppressing the common-mode voltage; this contributes to improving the performance of two-level voltage source inverters and enhancing their applicability for connecting the renewable energies to the grid.