Converter Control Research Articles

Research on static voltage stability enhancement for new energy station based on grid-forming control strategy

The advent of novel power systems has given rise to a multitude of safety and stability concerns associated with the integration of emerging energy sources and power electronic equipment. The active support of the grid-forming control strategy represents an effective solution to the voltage and frequency stability issues associated with the weak damping and low inertia inherent to high-ratio new energy systems. Firstly, a static voltage stability index based on critical impedance is proposed for assessment of the static stability margin of a new energy grid-connected system, based on the static voltage stability theory of a traditional single-unit single-load system. Secondly, an analysis is conducted of the control principle of the grid-forming control converter and its impedance characteristics. In conclusion, a method for enhancing the static voltage stability margin of grid-connected new energy stations through parameter control of grid-forming converters is presented. The simulation verification of the single-feed and multi-feed systems demonstrates the efficacy and accuracy of the methodology presented in this study.

Control of Large Wind Energy Converters for Aeroacoustic Noise Mitigation with Minimal Power Reduction

The population is often opposed to wind turbines being erected near their homes, mainly because the machines are noisy, especially at night. In an effort to establish a compromise between the needs of the people and the fulfilment of energy demands, wind turbines have the ability to switch between day and night operation by reducing the rotation speed during the night, resulting in a loss of generated power. The present study investigates simple models for noise emission, propagation, and prediction, with the objective of proposing a control system configuration that continuously adjusts the rotational speed as much as necessary until it matches sound level regulations while minimising power losses. Thus, several approaches are implemented and tested with a very large reference wind turbine. The simulation results of a reference wind turbine show that the approaches provide significant improvements in sound reduction as well as in power conversion.

Second‐Harmonic Ripple in Two‐Stage Single‐Phase Photovoltaic Inverters: Analysis and Mitigation

ABSTRACTTwo‐stage single‐phase photovoltaic inverters exhibit a second‐harmonic ripple at the dc‐link voltage, which can cause variations in the terminal voltage of the photovoltaic array, reducing the efficiency of the maximum power point tracking (MPPT). Initially, this work investigates the efficiency reduction caused by the second‐harmonic component using analytical models. Besides, this work explores a control technique to reduce the ripple in the terminals of the photovoltaic module based on real‐time normalization of the dc/dc converter control signal. This technique is compared with conventional control and with the addition of second‐harmonic resonant control. The case study is based on a 4.4‐kVA/220‐V photovoltaic inverter with input for two photovoltaic strings. The results indicate that both techniques are capable of performing the attenuation of the voltage ripple at the terminals of the photovoltaic array, resulting in efficiency gains in the order of 0.74% for the strategy based on resonant control and 0.95% for the proposed normalization technique. In addition, C‐HIL and experimental results prove the reduction in voltage ripple with the normalization and resonant control. As an advantage, the normalization technique is simpler than the second one, because it does not require modification of the control structure of the dc/dc converter.

Study on Control of Electronic Frequency Converters for Continuous Operation in the Event of a Short-Circuit Fault at Feeding Circuit in Independent Operation

Study on Control of Electronic Frequency Converters for Continuous Operation in the Event of a Short-Circuit Fault at Feeding Circuit in Independent Operation

Model predictive power control for grid-tied T-type three-level quasi-Z-source inverter with low complexity

Abstract The appealing design known as T-type three-level quasi-Z-source inverters (T2LQZSI) can function in both step-down and step-up modes. Model predictive control for converters has also received a lot of interest. This article suggests a low-complexity model predictive power control for T-type quasi-Z-source inverters with neutral-point voltage (NP-V) balance to address the shortcomings of conventional model predictive control and achieve improved performance. The resulting voltage is produced by using a variety of vectors. For NP-V balance, the tiny vector is employed. In addition, a strong optimum sector selection approach is suggested, which significantly lowers the processing complexity. Results from experiments show how effective and better the suggested technique is.

Arduino performance in control systems for converting air-to-water

Humans are unable to function without water. Water is therefore necessary for living. This study will address the advantages of converting air into drinkable water based on this premise. Regarding the condensation process itself, it is not the best option to use it in remote locations because it needs a lot of energy and equipment. Consequently, thermoelectric technology was used in this study to replace the condensation process. This tool's easier thermoelectric operation makes it suitable for usage in remote locations. The design of an effective Arduino program control system should take into account the effects of temperature and humidity condition parameters on the environment to maximize water production. This will allow the performance between supporting sensors and the main components to be automatically optimized under a variety of environmental conditions and produce water without wasting excessive energy. As a result, the trial where the average temperature was 30°C and the average humidity was 81% produced the highest results for the researchers when they calculated the environmental condition factors that were already known. Within the hour-long study session, 6 milliliters of water were created. In addition to the efficiency with which the Arduino program is commanded, from all sensors to the primary thermoelectric components, it can execute commands automatically and optimally. It can also resolve issues that affect the air-to-water converter controller's performance in a way that ensures proper operation of all controllers by taking into account the relevant factors. to the fullest without squandering too much energy

Pulse current stabilizer with digital control for the power supply system of the plasmatron

Purpose. Solution of theoretical and practical problems on providing digital control of a pulse converter using high-speed microprocessor tools in the output current stabilization mode with provision of a specified duration of transient processes caused by an increase in load voltage and output current astaticity, which allows to obtain significant advantages over analog versions. Methodology. Review of literary and patent sources on the subject, theory of pulse automatic control systems, mathematical modeling of processes in pulse current stabilizers in the MATLAB / Simulink software environment and physical prototyping. Findings. A simulation model of an autonomous power supply system based on a converter using soft switching technology of transistors and an arc load is presented. A control law is synthesized and a model of a pulse current stabilizer is developed. A method is proposed and ways are found to control a pulse current stabilizer that provide a given duration of transients and astatism of the output current. A model of a pulse stabilizer with digital control based on a single-crystal computing module is developed and manufactured. The results of the study confirm the achievement of a finite duration of transient processes caused by a step change in the load voltage, close to 3-4 periods of conversion and output current astaticism. It is shown that the use of a pulse stabilizer using a fully digital control circuit has undeniable advantages over analog systems. Originality. The problem of synthesizing a digital controller for a given control time by the method of desired transfer functions for a soft switching operating converter on an arc load is solved. In addition to the given control time, additional quality requirements in the steady state are provided. Practical value.The use of microprocessor technology makes it possible not only to implement complex and new highly efficient control algorithms for a converter operating in the pulse current stabilizer mode, but also to perform additional functions for overload protection, self-diagnostics and telemetry of pulse converters. The use of this same digital device simultaneously for the purpose of controlling a pulse converter will allow to abandon analog PWM controllers and thereby reduce its own energy consumption and weight and size characteristics, increase the reliability of the functioning of pulse converters in power supply systems as a whole.

Development of a control algorithm for a boost converter with the possibility of dynamic correction of control system parameters

RELEVANCE of the study lies in the development of an algorithm for controlling a DC voltage converter capable of providing a high-quality transient process with a wide change in the input parameters of the control object, affecting its nonlinear properties. purpose. THE PURPOSE. To consider methods for the development of continuous and discrete control systems for a step-up DC voltage converter and to obtain an analytical dependence of accounting for the nonlinear properties of the converter that affect the quality of regulation of the output voltage of the voltage stabilizer METHODS. The method of the average geometric root was chosen as a method for calculating the coefficients of the DC voltage converter control system, and the current circuit is adjusted using the technical optimum method, and the voltage circuit using the symmetric optimum method. The obtained analytical solutions of mathematical models and simulation models were compared in the SimInTech software environment. results. RESULTS. The simulation results show that the analytical solution of the mathematical model of the voltage stabilization system has a shorter transition time than the simulation results. This is due to the fact that in the mathematical model according to which the continuous control algorithm was synthesized, the presence of a power input filter, as well as the degree of their precharge, is not taken into account. Because of this, the transition time on simulation models is slower, applied 4 times than in the mathematical model. conclusion. CONCLUSION. When comparing the algorithms with each other, it can be seen that the algorithm obtained by converting a continuous algorithm by the Tusten method has the shortest transition time than all other algorithms. The continuous algorithm and the algorithm obtained by the inverse Euler transformation method have a speed close to each other, and the algorithm obtained by the direct Euler transformation turns out to be the slowest.

Optimal Control of FSBB Converter with Aquila Optimizer-Based PID Controller

This paper presents a new methodology for determining the optimal coefficients of a PID controller for a four-switch buck–boost (FSBB) converter. The main objective of this research is to improve the performance of FSBB converters by fine-tuning the parameters of the PID controller using the newly developed Aquila Optimizer (AO). PID controllers are widely recognized for their simple yet effective control in FSBB converters. However, to further improve the efficiency and reliability of the control system, the PID control parameters must be optimized. In this context, the application of the AO algorithm proves to be a significant advance. By optimizing the PID coefficients, the dynamic responsiveness of the system can be improved, thus reducing the response time. In addition, the robustness of the control system is enhanced, which is essential to ensure stable and reliable operation under varying conditions. The use of AOs plays a key role in maintaining system stability and ensuring the proper operation of the control system even under challenging conditions. In order to demonstrate the effectiveness and potential of the proposed method, the performance of the AO-optimized PID controller was compared with that of PID controllers tuned by other optimization algorithms in the same test environment. The results show that the AO outperforms the other optimization algorithms in terms of dynamic response and robustness, thus validating the efficiency and correctness of the proposed method. This work highlights the advantages of using the Aquila Optimizer in the PID tuning of FSBB converters, providing a promising solution for improving system performance.

Extreme learning machine based on BDE feature selection to detect fault scenarios in grid-connected PV systems under MPPT mode

This paper considers real-time data-driven adaptive fault detection (FD) in grid-connected PV (GPV) systems under maximum power point tracking (MPPT) modes during large variations. Faults under MPPT modes remain undetected for longer periods, introducing new protection challenges and threats to the system. An intelligent FD algorithm is developed through real-time multi-sensor measurements and virtual Micro Phasor Measurement Unit (Micro-PMU) estimations. The high-dimensional and high-frequency multivariate features vary over time, and computational efficiency becomes crucial to realizing online adaptive FD. The goal of this study is to present an artificial intelligence (AI) technique for detecting seven faults: inverter fault, feedback sensor fault, grid anomaly, nonhomogeneous partial shading, open circuit in PV array, MPPT controller fault, and boost converter controller fault. In this work, it was found that the application of Extreme Learning Machine (ELM) plays an important role in fault detection and localization. Nine (9) statistical features and eight (8) wavelet packet parameters are extracted from the data based on multiple default values. These features were used as an input vector to train and test the ELM and determine whether the system is operating under normal conditions or is faulty. The BDE feature selection algorithm is adopted to optimize the seven-fault classification procedure to reduce the number of features. The results showed that the Extreme Learning Machine (ELM), based on statistical parameters followed by BDE, can detect faults with high accuracy (98.3%) compared to a case without optimization.

Novel Droop-Based Techniques for Dynamic Performance Improvement in a Linear Active Disturbance Rejection Controlled-Dual Active Bridge for Fast Battery Charging of Electric Vehicles

Electric vehicles (EVs) are rapidly replacing fossil-fuel-powered vehicles, creating a need for a fast-charging infrastructure that is crucial for their widespread adoption. This research addresses this challenge by improving the control of dual active bridge converters, a popular choice for high-power EV charging stations. A critical issue in EV battery charging is the smooth transition between charging stages (constant current and constant voltage) which can disrupt converter performance. This work proposes a novel feedforward control method using a combination of droop-based techniques combined with a sophisticated linear active disturbance rejection control system applied to a single-phase shift-modulated dual active bridge. This combination ensures a seamless transition between charging stages and enhances the robustness of the system against fluctuations in both input voltage and load. Numerical simulations using MATLAB/Simulink R2024a demonstrated that this approach not only enables smooth charging but also reduces the peak input converter current, allowing for the use of lower-rated components in the converter design. This translates to potentially lower costs for building these essential charging stations and faster adoption of EVs.

Advanced Methods for Verifying Memory Controllers in Modern Computing Systems

The primary component of the computer system that requires enhancement is the memory's performance. A memory controller helps in the management of control between the memory as well as the processor. This study gives a general outline of how controller performance in systems based on power converters may be improved using AI approaches. Among the many uses for power converters in today's electrical and energy systems are the effective control and conversion of energy in electric cars, renewable energy sources, and industrial automation, among others. Complementary control strategies used in classical approaches, although work well, may experience difficulties when it comes to system complication, change, and unpredictability. To overcome these restrictions, artificial intelligence methods appear rather prospective. Among the AI types one can distinguish neural networks, fuzzy logic, machine learning that may help to control the converters with enhanced efficiency by using adaptive and intelligent control. These approaches enhance control precision, succession, and reaction time to enhance system effectiveness and dependability. Moreover, this integration of AI enhances the most power converters by making it easier to predict maintenance, detect faults, and optimise for energy hence enhancing the systems. The paper presents new trends in the advanced smart control of the power converters, total control techniques, advantages as well as the challenges posed by AI control strategies. It also describes future trends and research areas for achieving enhanced performance in power converter-based systems through AI and Control techniques

Research on Cascaded On‐Board DC/DC Converter Based on Three‐Phase Interleaved LLC

ABSTRACTThe on‐board DC/DC converter proposed in this research consists of a Buck converter and a three‐phase interleaved LLC resonant converter. This paper analyzes the average current and output current ripple characteristics of the rear‐stage converter in addition to explaining the topology and working principles of the front‐stage Buck converter and the rear‐stage three‐phase interleaved LLC resonant converter. To establish a single‐phase fundamental equivalent circuit for the rear‐stage converter, apply the fundamental wave analysis method, and it is essential for comprehending the impact of relevant system parameters on voltage gain characteristics and resonant operating regions. Conducting research on the two‐stage on‐board DC/DC converter's control strategy involves establishing small‐signal circuit models for both front and rear stage converters, derivation of parameters for double closed‐loop control, and determination of the control strategy employing phase‐shifted current sharing for the rear‐stage converter in cases where significant tolerance exists in resonant components. The simulation for a two‐stage on‐board DC/DC converter results indicates that under various conditions of resonant component tolerance, the converter is capable of achieving balanced phase currents and demonstrates minimal output current ripple prior to capacitor filtering. A 1.5‐kW experimental prototype has been fabricated, and the experimental findings indicate that the output voltage remains stable at 13.8 V despite fluctuations in input voltage. The highest efficiency of the prototype is about 96.27%, and the utilization of phase‐shifting current balancing control results in a notable reduction in output current ripple. This provides more evidence that the design of a two‐stage on‐board DC/DC converter is correct.

Design, and dynamic evaluation of a novel photovoltaic pumping system emulation with DS1104 hardware setup: Towards innovative in green energy systems.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose's challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator's ability to faithfully reproduce genuine solar panel characteristics.

Resonance Suppression Method Based on Hybrid Damping Linear Active Disturbance Rejection Control for Multi-Parallel Converters

The parallel operation of multiple LCL-type converters will result in a deviation of the resonant frequency and resonance phenomena. The occurrence of harmonic resonance can cause problems such as an increase in harmonic voltage and current. This can lead to the malfunction of relay protection and automatic devices, causing damage to system equipment. In severe cases, it can cause accidents and threaten the safe operation of the power system. A hybrid damping active disturbance rejection control (HD-ADRC) method is proposed in this paper to suppress the harmonic resonance of parallel LCL-type converters. First, a third-order linear disturbance rejection controller (LADRC) including the linear extended-state observer and the error-feedback control rate is designed based on LCL-type converter model analysis. The proposed method considers the resonance couplings caused by both internal and external disturbances as the total disturbance, thus improving the anti-disturbance capabilities as well as the operational stability of converters in parallel. Then, a hybrid damping control is proposed to reconstruct the damping characteristics of converters to suppress the parallel resonance spike and reduce the resonance frequency offset. And the parameter selection of the control system is optimized through a stability analysis of the tracking performance and anti-disturbance performance of the HD-ADRC controller. Finally, all the theoretical considerations are verified by simulation and experimental results based on the Matlab/Simulink 2018B and dSpace platform. The simulation and experimental results show that the PI controller gives a THD of 5.33%, which is reduced to 4.66% by employing the HD-LADRC, indicating an improved decoupling between the converters working in parallel with the proposed control scheme.

Partial Fluctuation Power Control of Resonant Converter in Solid-State Transformer

Partial Fluctuation Power Control of Resonant Converter in Solid-State Transformer

Finite Control Set Model Predictive Control for Grid-Connected Parallel Power Converters With Guaranteed Optimality

Finite Control Set Model Predictive Control for Grid-Connected Parallel Power Converters With Guaranteed Optimality

Analysis and Control of a Three-Port Converter With High-Frequency AC Link for Hybrid Unmanned/Autonomous Aerial Vehicles

Analysis and Control of a Three-Port Converter With High-Frequency AC Link for Hybrid Unmanned/Autonomous Aerial Vehicles

Current-Oriented Phase-Locked Loop Method for Robust Control of Grid-Connected Converter in Extremely Weak Grid

Current-Oriented Phase-Locked Loop Method for Robust Control of Grid-Connected Converter in Extremely Weak Grid

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters

Design and Tank Testing of Reinforcement Learning Control for Wave Energy Converters