This article presents an autonomous control architecture for grid-interactive inverters, focusing on the inverters providing power in a microgrid during utility outages. In scenarios where the microgrid becomes isolated from the utility grid, achieving load sharing among inverters, typically via droop controls, and restoring frequency and voltage amplitude become essential tasks. When the microgrid is ready to reconnect with the utility grid, a synchrocheck relay verifies synchronization, assuming the inverters have already restored voltage and frequency to the nominal levels. Before reconnection, an automatic tap-changer transformer can correct minor voltage discrepancies on both sides of the relay (circuit-breaker). This article introduces a novel method that enables inverters to autonomously detect utility grid reconnection without relying on communication, transferring from grid-forming (GFM) to grid-following (GFL) mode. The control architecture employs a direct controller for inverters, implementing a control-sync technique featuring two parallel control paths with minimal control loops, facilitating seamless transitions between GFM and GFL modes. To validate the effectiveness of this control architecture, experiments were conducted using a 30-kVA grid emulator and three 5–10 kVA, 208-V three-phase inverters. The results offer valuable insights into the practical implementation and demonstrate performance of the proposed controller.

This article provides insights into the dynamic performance of indirect and direct control strategies for grid-forming (GFM) inverters. The indirect method for grid-forming inverters utilizes three cascaded stages to produce the reference signal sent to the PWM generator. However, the direct method has only one stage. The indirect method consists of the outer loop, which controls the power, the middle loop, which requlates voltage, and the inner loop, which controls the output current. The direct method does not require the middle and inner control loops. The article compares the performance and sensitivity of both indirect and direct control methods under various conditions, including static, inductive and dynamic loads, by adjusting controller gain parameters. A virtual reactance inrush current mitigation technique is implemented with the direct method to provide momentary control over inrush caused by the dynamic loads. The direct method incorporates a feedforward technique known as virtual reactance inrush current mitigation to outperform the performance of the direct control method in the presence of dynamic and inductive loads. The performance of both control methods is experimentally compared, and the direct method outperforms the indirect method. Experimental analyses are performed in a laboratory-scaled microgrid supplied by a 208V, one 5kVA SiC inverter, and one 10kVA Si-based inverter to compare the performance of the indirect and direct methods under different test scenarios, and the outcomes are presented in this article.

A new sliding-mode-control-based power conversion scheme is proposed for photovoltaic energy conversion systems. The perturbation and observation (P&O) maximum power-point tracking (MPPT) approach is adopted for optimizing the power generation capabilities from solar panels. Due to the inherent nonlinear dynamics of power converters, we need to adopt a nonlinear control approach to optimize the energy conversion efficiency and tolerate the fluctuations and changes of load and sunlight irradiance. In this manuscript, novel first-and higher-order sliding mode control approaches are proposed, aiming to provide a systematic approach for the robust and optimal control of solar energy conversion, which guarantees Lyapunov stability and consistent performance in the face of external perturbations and disturbances. Moreover, to eliminate the chattering phenomenon inherent in the first-order approach, super-twisting second-order sliding mode control is developed for the buck-boost converter. Furthermore, the output of DC–DC converter supplies a voltage-oriented-control (VOC)-based space-vector pulse-width-modulated inverter to generate three-phase AC power to the grid. To demonstrate the robustness and effectiveness of the proposed scheme, computer simulations and dSPACE hardware-in-the-loop platform have been carried on for examining the proposed sliding-mode-control-based solar energy conversion system.

Grid-interactive inverters are mainly employed to optimize power injection while synchronizing with the grid's frequency and using the phase angle as the reference point. In certain circumstances, these inverters might be required to sustain power in an isolated grid segment. To achieve this, they need to generate reference points internally and collaboratively share the power load of the islanded segment, known as a microgrid. This article presents a self-governing control architecture for inverters that autonomously detect grid reconnection and islanding events, switching between grid-following (GFL) and grid-forming (GFM) modes without relying on data communication or supervisory controllers. The proposed control architecture employs a unique control-sync technique in which two sets of parallel control paths with minimal control loops are used for GFL and GFM modes of operations. Herein, while one set of control paths is engaged to generate the pulse-width modulated (PWM) signals, the other set synchronizes in the background. This ensures seamless transitions between GFL and GFM modes of operation. The efficacy of the proposed autonomous control scheme is validated through a hardware setup comprising a 30 kVA grid emulator and three 5 - 10 kVA, 208V three-phase inverters. The experiment results confirm that inverters with the proposed controller can detect grid reconnection and islanding events and autonomously switch between GFL and GFM modes.

The capability to exchange information with utility operators, aggregators, and nearby smart devices can make a grid-interactive inverter an intelligent cyber-physical device. However, the capability of exchanging information can also put the inverters at the risk of insecure operation. In this paper, possible software manipulations into the inverters are studied to understand their vulnerability to cyber-attacks. Moreover, the state-of-the-art system-level and device-level cyber-defense measures are discussed, and advantages and drawbacks of each technique are provided. Studies show that a reference model can be implemented in device-level security to effectively examine incoming setpoints for detecting and preventing malicious or harmful actions. This paper particularly underlines the significance of device-level self-security and its advantages for grid-interactive inverters. Finally, recommendations for future studies are provided.

This article presents the concept of self-protective inverters using steady-state and dynamic reference models. The self-protection strategy inspects incoming setpoints from the utility operator or third-party aggregators using analytical reference models before engaging the setpoints to the inverter's local controller. When a malicious setpoint passes the existing security layers, a smart inverter can examine the integrity of an incoming setpoint in real-time. The efficacy of the self-protection strategy has been tested using a laboratory setup, including a three-phase 3 kVA inverter and a 12 kW regenerative grid emulator. The results verify that the analytical steady-state and dynamic models can provide device-level protection for grid-interactive inverters by preventing harmful setpoints from getting engaged to the local controller.