This paper proposes an optimal power-sharing algorithm (OPSA) devised to regulate the power distribution among grid-forming inverters (GFMIs) in modern power systems powered by distributed energy resources (DERs). Unlike traditional power-sharing techniques that assume an infinite or constant power supply, OPSA continuously modifies virtual impedance based on resource availability, such as the battery capacity and state of charge (SOC). The supervisory controller integrating OPSA calculates the demanded power to adjust the virtual impedance, which is optimally distributed among the GFMIs, minimizing battery stress and promoting balanced discharge. Furthermore, the proposed approach improves grid resiliency by dynamically adapting to changing load variations and mitigating potential instabilities. Finally, the effectiveness of the OPSA is validated by the simulation results of multiple test scenarios across varying operating conditions.

The integration of solid-state transformers (SSTs) with grid-forming inverters (GFMIs) improves flexibility and control in modern microgrids while simultaneously introducing new cyber-physical vulnerabilities. The strong coupling between SSTs and GFMIs creates dynamics that result in the diffusion of localized cyberattacks throughout the microgrid. This paper provides a comprehensive impact analysis of four representative cyberattack scenarios: side-channel noise intrusion (SNI) compromising the integrity of SST measurement feedback, tampering with the voltage-regulation loop of the SST, a virtual governor frequency-restoration attack on GFMI, and cascaded tripping of breakers simulating insider access to protection coordination. The attacks are targeted towards specific control or protection layers and are evaluated through simulations on a modified IEEE 14-bus system. Results demonstrate that even brief attacks can result in prolonged instability, including frequency deviations, power oscillations, and voltage regulation failures, due to the low inertia and damping of power electronic-based systems. Furthermore, the coupling between the SST and the GFMIs results in aftereffects even well beyond the removal of the attack, degrading overall system. The findings underscore the importance of recognizing control-layer cyber threats in power electronic-dominated microgrids and motivate the need for more resilient control architectures.

Virtual impedance-based power sharing between several interconnected grid-forming inverters (GFMI)s in a power electronics-dominated grid (PEDG) does not consider the available power reserves. This non-optimal power-sharing may result in the overloading of nearby inverter-based resources (IBR)s exhibiting lower effective line impedances in the network. This paper proposes an optimal and controllable power-sharing scheme based on a modular artificial neural network (ANN) that can consider various factors like power reserve, line losses, incentives from the grid, etc., and increases the system's scalability. An optimum power allocator (OPA) mechanism that monitors the output active powers and line losses of all the IBRs is proposed to address the issue of uncontrolled power sharing. The OPA dynamically adjusts power allocation weights using linear programming to optimize the overall loss minimization cost function. Moreover, an artificial neural network-based virtual impedance optimizer (ANN-VIO) is also proposed, which estimates the corresponding virtual impedance (VI) value for each GFMI unit in the PEDG. The primary controller of GFMI uses these estimated VI values to adjust its point of common coupling (PCC) voltage reference and attain optimum proportionate power sharing within the overall PEDG. Multiple case studies are performed to validate the effectiveness of the proposed GFMIs power-sharing scheme.

Power electronics dominated grid (PEDG) consisting of multiple inter-connected distributed generation (DG) units are getting more popular because of their benefits in reducing the stress on main transmission lines, limiting line losses, and improving the efficiency and stability of the power system. Often a PEDG is comprised of several energy sources such as solar, wind, and energy storage devices. For that reason, optimal power sharing between all the sources is crucial to enhance the reliability and resiliency of the network. Hence, this paper provides comprehensive insights into the operation and working principles, limitations, and challenges of the power-sharing schemes employed in PEDG. More specifically, control laws of the droop, virtual synchronous generator (VSG), and Lienard and Consensus-based oscillators are briefly overviewed. In addition, the inherent drawbacks and challenges of existing power-sharing schemes are explained for inductive, resistive, and complex line impedances. Moreover, their performance under dynamic variations of the source availability, inverter power reserve, line losses, and generation costs are discussed in detail.