Inverter Control Research Articles

Research on Optimized Multi‐Objective FCS‐MPC Without Weighting Factors of NPC Three‐Level Inverter

ABSTRACTTo address a series of issues in the application of finite control set model predictive control (FCS‐MPC) strategy for neutral point clamped (NPC) three‐level inverters, such as large amount of rolling optimization calculation, poor midpoint voltage balance effect, high common mode voltage, and complex design of weighting coefficients, this paper proposes an optimized multi‐objective FCS‐MPC strategy without weighting factors. First, the method applies the idea of space vector region division, to obtain the optimal region based on Lyapunov function, and combines with delay compensation, reducing the system's optimization time and enhancing the control precision of the system. Second, aiming at the issue of multi‐objective control for inverters, by constructing the objective function to control tracking reference current, midpoint voltage balance, and reduce common mode voltage, a hierarchical optimization control method is adopted. This approach eliminates the need to design complex weighting coefficients constrained in the objective function as constraints, thereby improving the accuracy of predicted currents. Finally, the optimized multi‐objective FCS‐MPC control strategy is validated through simulation and experimentation to achieve a better balance of midpoint voltage and reduce common mode voltage and harmonic content, thereby enhancing the control precision and dynamic/static performance of the system.

A Novel Reinforcement Learning Algorithm-Based Control Strategy for Grid-Configured Inverters

To address the power oscillation problem due to the introduction of inertia and damping, this paper proposes a new deep reinforcement learning algorithm based on the SD3 (Softmax Deep Double Deterministic policy gradients) algorithm for grid configuration inverter control strategy to compensate for the loss of inertia and damping in the grid. Virtual synchronous generator control, as a typical grid configuration technique, inevitably brings stability problems while providing inertia and damping support to the grid. In this paper, we first analyze the nonlinear relationship between inertia and angular velocity, and find the key parameters to maintain the power stability; then, we migrate the deep reinforcement learning strategy, and design the control strategy applicable to the virtual synchronous generator; finally, through the adaption of the key parameters, we combine the control strategy with the grid-connected inverter, and solve the problem of the excessive grid-connected power oscillation of the inverter. The effectiveness and accuracy of the control method compared with other algorithms are verified by building a simulation model in MATLAB/Simulink, which realizes the purpose of reducing power oscillation.

Design and Practical Implementation of Microgrid Inverter Control Using TMS320F28335 Microcontroller with Improvement in Electrical Power Quality

Nowadays, the proliferation of distributed renewable energy sources is a fact. A microgrid is a good solution to self-manage the energy generation and consumption of electrical loads and sources from the point of view of the consumer as well as the power system operator. To make a microgrid as versatile as necessary to carry that out, a flexible inverter is necessary. In this paper, an algorithm is presented to control an inverter and make it complete and versatile to work in grid-connected and in isolated modes, injecting or receiving power from the grid and always compensating the harmonics generated by the loads in the microgrid. With this inverter, the microgrid can work while optimizing its energy consumption or according to the power system operator instructions. The inverter proposed is tested in a designed Matlab/Simulink simulation platform. After that, an experimental platform designed and built ad hoc, including a DC source, AC linear and non-linear loads, and a Semikron power inverter, is used to test the proposed control strategies. The results corroborate the good system performance. The replicability of the system is guaranteed by the use of low-cost devices in the implementation of the control.

Versatile LCL Inverter Model for Controlled Inverter Operation in Transient Grid Calculation Using the Extended Node Method

Due to increasing decentralized power applications, power electronics are gaining importance, also in distribution grids. Since their scope of investigation is diverse, their versatile models and their use in grid calculations are important. In this work, a three-phase grid-synchronous inverter with an LCL filter is considered. It is defined as a component of the "Extended Node Method" to make it applicable in this node-based transient grid calculation method. Because the component stucture always looks the same and the construction of the grid system of equations always follows the same, straightforward process, the model can be applied easily and several times to large network calculations. Furthermore, an approach is developed for how inverter control algorithms are interconnected with the method’s results in the time domain. This allows for the fast analysis of converter control schemes in different grid topologies. To evaluate its accuracy, the developed approach is compared to equivalent calculations with Simulink and shows very good agreement, also for steep transients. In the long term, this model is intended to bridge the gap to other DC systems like electrochemical components and to gas and heating networks with the Extended Node Method.

Model-Free Resilient Grid-Forming and Grid-Following Inverter Control Against Cyberattacks Using Reinforcement Learning

The U.S. movement toward clean energy generation has increased the number of installed inverter-based resources (IBR) in the grid, introducing new challenges in IBR control and cybersecurity. IBRs receive their set point through the communication link, which may expose them to cyber threats. Previous work has developed various techniques to detect and mitigate cyberattacks on IBRs, developing schemes for new inverters being installed in the grid. This work focuses on developing model-free control techniques for already installed IBR in the grid without the need to access IBR internal control parameters. The proposed method is tested for both the grid-forming and grid-following inverter control. Different detection and mitigation algorithms are used to enhance the accuracy of the proposed method. The proposed method is tested using the modified CIGRE 14-bus North American grid with seven IBRs in PSCAD/EMTDC. Finally, the performance of the detection algorithm is tested under grid normal transients, such as set point change, load change, and short-circuit fault, to make sure the proposed detection method does not provide false positives.

Improving LV networks hosting capacity via the use of residential P-Q inverter control – a Monte-Carlo analysis

Improving LV networks hosting capacity via the use of residential P-Q inverter control – a Monte-Carlo analysis

Topology Construction, Modeling, and Control of Multi-level Inverters without shoot-through problem

Topology Construction, Modeling, and Control of Multi-level Inverters without shoot-through problem

Control and Stability Analysis of Grid-Connected Inverters in an Unbalanced and Distorted Weak Grid using MDSOGI Based Selective Virtual Impedance

Control and Stability Analysis of Grid-Connected Inverters in an Unbalanced and Distorted Weak Grid using MDSOGI Based Selective Virtual Impedance

Grid power quality enhancement by nonlinear control of voltage source inverter

Aim/Background: Maintaining power quality in grid-connected systems with renewable energy sources, particularly solar, is a significant challenge due to stringent requirements for harmonic mitigation. Voltage source inverters serve as critical interfaces between the grid and renewable energy sources but require robust control strategies to ensure power quality. Methods: This study integrates renewable energy resources and DC micro-grids on the same bus and designs a shunt active power filter (SAPF) based on synchronous reference frame theory. The SAPF is compared with an instantaneous power theory-based controller. MATLAB simulations are conducted to test the performance under different nonlinear load conditions. Results: The synchronous reference frame theory-based controller demonstrated superior performance, with high efficiency, simplicity, and fast response. It reduced total harmonic distortion (THD) in the grid to 1.59% and 0.19% when connecting two nonlinear loads, compared to 1.66% and 1.62% for the instantaneous power theory-based controller. The SAPF effectively detected abnormal behavior, removed harmonics caused by non-linear loads, and improved the power factor. Conclusion: The synchronous reference frame theory-based SAPF is a reliable solution for enhancing grid power quality by mitigating harmonics and maintaining the desired compensation. Its superior performance highlights its suitability for applications involving renewable energy integration with the grid.

Improving photovoltaic hosting capacity of distribution networks with coordinated inverter control: A case study of the EPRI J1 feeder

Improving photovoltaic hosting capacity of distribution networks with coordinated inverter control: A case study of the EPRI J1 feeder

SoC–Based Inverter Control Strategy for Grid‐Connected Battery Energy Storage in AC Microgrid

The successful integration of battery energy storage systems (BESSs) is crucial for enhancing the resilience and performance of microgrids (MGs) and power systems. This study introduces a control strategy designed to optimize the operation of BESSs. This control strategy optimizes the BESS operation by dynamically adjusting the inverter’s power reference, thereby, extending the battery cycle life. This approach incorporates a droop control mechanism that adjusts control actions in response to state‐of‐charge (SoC) fluctuations of the BESSs, thereby, enhancing system performance. The effectiveness of this SoC–based control strategy is demonstrated through Matlab/Simulink. It shows its capabilities in regulating power, voltage, grid synchronization, and stability. The paper utilizes a modified CIGRE MG benchmark for system evaluation. It presents case studies to demonstrate the effectiveness of the proposed control modifications. Additionally, a comparative analysis with a power–voltage (P–V) control strategy is presented. This analysis highlights the advantages of the proposed strategy in ensuring stable voltage regulation within the MG. This research provides a robust foundation for future developments in optimizing BESS integration. It offers a roadmap to advance the efficiency, reliability, and longevity of battery‐based solutions in the evolving landscape of sustainable energy systems. Additionally, it sheds light on the potential for scalability and applicability across diverse MG configurations and operational scenarios.

Multi-Fault-Tolerant Operation of Grid-Interfaced Photovoltaic Inverters Using Twin Delayed Deep Deterministic Policy Gradient Agent

The elevated penetration of renewable energy has seen a significant increase in the integration of inverter-based resources (IBRs) into the electricity network. According to various industrial standards on interconnection and interoperability, IBRs should be able to withstand variability in grid conditions. Positive sequence voltage-oriented control (PSVOC) with a feed-forward decoupling approach is often adopted to ensure closed-loop control of inverters. However, the dynamic response of this control scheme deteriorates during fluctuations in the grid voltage due to the sensitivity of proportional–integral controllers, the presence of the direct- and quadrature-axis voltage terms in the cross-coupling, and predefined saturation limits. As such, a twin delayed deep deterministic policy gradient-based voltage-oriented control (TD3VOC) is formulated and trained to provide effective current control of inverter-based resources under various dynamic conditions of the grid through transfer learning. The actor–critic-based reinforcement learning agent is designed and trained using the model-free Markov decision process through interaction with a grid-connected photovoltaic inverter environment developed in MATLAB/Simulink® 2023b. Using the standard PSVOC method results in inverter input voltage overshoots of up to 2.50 p.u., with post-fault current restoration times of as high as 0.55 s during asymmetrical faults. The designed TD3VOC technique confines the DC link voltage overshoot to 1.05 p.u. and achieves a low current recovery duration of 0.01 s after fault clearance. In the event of a severe symmetric fault, the conventional control method is unable to restore the inverter operation, leading to integral-time absolute errors of 0.60 and 0.32 for the currents of the d and q axes, respectively. The newly proposed agent-based control strategy restricts cumulative errors to 0.03 and 0.09 for the d and q axes, respectively, thus improving inverter regulation. The results indicate the superior performance of the proposed control scheme in maintaining the stability of the inverter DC link bus voltage, reducing post-fault system recovery time, and limiting negative sequence currents during severe asymmetrical and symmetrical grid faults compared with the conventional PSVOC approach.

Improved Genetic Algorithm-Based Harmonic Mitigation Control of an Asymmetrical Dual-Source 13-Level Switched-Capacitor Multilevel Inverter

A single-phase multilevel inverter with a switched-capacitor multilevel (SC-MLI) configuration is developed to provide 13-level output voltages. An improved genetic algorithm (GA) with adaptive mutation and crossover rates is employed to achieve robust harmonic mitigation by avoiding local optima and ensuring optimal performance. The topology introduces an SC-MLI that generates AC output voltage at desired levels using only two capacitors, two asymmetrical DC sources, one diode, and 11 switches. This allows the inverter to use fewer gate drivers and, hence, increases the power density of the converter. A significant challenge in the normal operation of SC-MLI circuits relates to the self-voltage balance of the capacitors, which easily becomes unstable, particularly at low modulation indices. The proposed design addresses this issue without the need for ancillary devices or complex control schemes, ensuring stable self-balanced operation across the entire spectrum of the modulation index. In this context, the harmonic mitigation technique optimized through GA applied in this inverter ensures low harmonic distortion, achieving a total harmonic distortion (THD) of 6.73%, thereby enhancing power quality even at low modulation indices. The performance of this SC-MLI is modeled under various loading scenarios using MATLAB/Simulink® with validation performed through an Opal-RT real-time emulator. Additionally, the inverter’s overall power losses and individual switch losses, along with the efficiency, are analyzed using the simulation tool PLEXIM-PLECS. Efficiency is found to be 96.62%.

Small signal stability enhancement using GFM-based inverter control integrated with wide area damping controller in solar integrated microgrid network

Small signal stability enhancement using GFM-based inverter control integrated with wide area damping controller in solar integrated microgrid network

Straightforward predictive direct power control for grid-connected ANPC inverter with flying capacitor voltage self-balancing

Improving control quality in inverter systems has attracted considerable attention, particularly in multilevel inverters for high-power applications. This study suggests a straightforward predictive direct power control system for a five-level Active Neutral Point Clamped inverter connected to the grid. The proposed method offers the benefit of reducing the heavy computational load by implementing a two-stage optimization process for the objective function. In contrast to the conventional finite control set model predictive control which involves comprehensive searches for all possible switching configurations within the iterative optimization process, the suggested approach focuses only on potential voltage vectors based on the desired inverter voltage’s location at the initial stage. Second, the self-balancing flying capacitor voltages are guaranteed by employing the duplicative switching states. Another advantage of the presented algorithm is an obviation of numerous selecting weighting factors. The effectiveness of the advanced strategy is confirmed through extensive comparative simulation and hardware-in-the-loop studies conducted in both conditions during stable states and transitions. Contrasted to the previous technique, this innovative method demonstrates an improvement in the grid’s power ripple and total harmonic distortion of the current by 14.66% and 19.58%. Furthermore, the computational time required for this method is significantly reduced by 64.58%, and 61.36% correlate to the traditional and other approaches, respectively. These results may facilitate the implementation of an effective control approach for multilevel inverters, employing a cost-effective control platform by a limited sampling interval.

Analysis of Hybrid Energy Modelling (Grid and Inverter Based Resources) Using Grid Following Inverter for the Integration of Renewable Energy Generation

The energy dependency of the grid will cause its own problems because the energy generated comes from fossil fuels. On the other hand, centralized electrification using renewable energy has a high risk on frequency and voltage stability. Renewable energy depends entirely on climate conditions and has no inertia to maintain stability. Hybrid energy between grids and Inverter Based Resources (IBRs) are alternative solutions used. The research applies an inverter control scheme to IBRs to be penetrated the grid. The research will apply a zero-export load with electricity requirements to be charged to renewable power plants using grid distribution networks. The inertia less properties of renewable energy will cause interference when combined with the power grid (synchronous generator). It will also be analyzed on this study by applying the following inverter scheme by paying attention to the phase angle and synchronization against the voltage, current and frequency variables of the grid. The results obtained in this study; renewable energy can contribute 90% to the load. This is due to the Losses factor and efficiency system in the plant. Renewable energy generators feed active power to the grid as well as support grids with a Total Harmonic Distortion (THD) indicator of <10%. In the design of this hybrid power system, it is done on MATLAB software with installation configuration in accordance with IEEE standards so that it can be a reference for the installation of real-condition renewable energies with grid. Keywords—Renewable Energy, Grid Following, Green Electricity, Hybrid Energy

Stability and Fault Detection Algorithm of Grid-Connected Inverter in Complex Power Grid Environment

In order to improve the stability, this paper designs a control strategy based on adaptive grid impedance. By monitoring the grid impedance in real time and dynamically adjusting the inverter control parameters, the influence of grid impedance change on inverter stability is effectively reduced. At the same time, LCL filter is introduced, which significantly filters out the higher harmonics in the inverter output current and improves the output waveform quality. In addition, a voltage compensation device is applied to quickly generate a compensation voltage signal when the grid voltage fluctuates to ensure the stability of the inverter output voltage. In the aspect of fault detection, a data-driven fault detection algorithm is proposed, which combines machine learning and real-time monitoring technology to realize early detection and accurate diagnosis of inverter faults by collecting and analyzing inverter operation data. The experimental results show that the algorithm performs well in the detection of power switch device faults, sensor faults and other types, and has high classification accuracy. The research shows that the control strategy based on adaptive grid impedance, the addition of LCL filter and the application of voltage compensation device have significantly improved the stability of grid-connected inverter in complex grid environment. The proposed data-driven fault detection algorithm provides strong support for rapid fault location and accurate treatment of inverter.

Simulation Analysis of Simulink-based Inverter Controller in Micro-grids

As environmental awareness increases and new energy technologies develop, microgrid systems have garnered significant attention as an important method for operating new energy sources. This trend reflects the growing emphasis on environmental protection. In the process of achieving both independent operation and grid-connected operation, the internal microgrid needs to incorporate an inverter control system equipped with various control methods. The inverter control system is responsible for regulating the inner loop parameters, and the coupling of these parameters will directly impact system stability. The research focus of this article is on microgrid systems that include wind-solar-storage systems. The study primarily employs three control types—constant power control (PQ), virtual synchronous generator control (VSG), and a combination of PQ and VSG control (PQ+VSG)—for simulation analysis to explore system stability. By conducting an in-depth stability analysis, we further understand the characteristics of inverter internal control and grid-connected inverter operation, thereby providing guidance for the design of control systems and ultimately achieving their effective application in power systems.

Signatures and Mechanism Analysis of Converter-Grid Subsynchronous Oscillations

In the last decade, a rather new phenomenon related to subsynchronous oscillations (SSO) in a wide frequency range has emerged in modern power grids with power converters. The consequences of these oscillations can be severe system accidents, which have already occurred in various power systems. Taking into account the importance of studying such oscillations for effective mitigation and the existing gaps in understanding the mechanisms of SSO occurrence due to different combinations of used controllers in the inverter control system, as well as the grid parameters, a frequency analysis of simplified grid inverter models is performed. As a result, five different mechanisms of SSO occurrence, the affecting factors and the level of inverter model detail required for the adequate study of SSO are justified. The developed detailed state–space model allowed for verifying the obtained results, as well as identifying an additional sixth mechanism of SSO occurrence. The common condition for the occurrence of all the identified SSO mechanisms is a weak grid with a short-circuit ratio of less than two. The results of control hardware-in-the-loop testing confirmed the conclusions drawn. As a result, a classification of SSO occurrence mechanisms was formed, reflecting their causes and distinctive features.

A comparative study of virtual synchronous generator and sinusoidal pulse width modulation in a wind high power conversion chain

The virtual synchronous generator (VSG) and sinusoidal pulse width modulation (SPWM) are two prominent control strategies that have attracted particular interest recently. In this paper, we compare these two inverter control strategies in a 5MW wind power conversion chain. The studied conversion chain includes a wind turbine, a permanent magnet synchronous generator, the power converters, namely the uncontrolled rectifier, and a two-stage inverter connected to the grid via an LCL filter. Our study of the two control methods shows that both strategies reduce the total harmonic distortion (THD) while respecting the grid connection conditions. The simulation results manifest that the VSG strategy has a better THD reduction of 0.99 % which is improved compared to the SPWM with a THD of 1.33%.