Grid-forming (GFM) inverters play a critical role in stabilizing future power grids. However, their synchronization is inherently coupled with frequency support, which poses a challenge to prevent overloading while maintaining synchronization. While existing literature has proposed strategies to mitigate the overload of GFM inverters during frequency excursions, these typically focus on limiting primary frequency regulation and overlook their inertial contribution, limiting their effectiveness. The present work addresses this gap by analyzing three overload mitigation strategies that dynamically adjust both primary frequency regulation and inertia. The main contribution of this work is formal analysis of the control structures, providing insight into the tuning process, dynamic behavior, and inherent trade-offs. The performance of these strategies is evaluated under grid frequency excursions and oscillations, focusing on their ability to limit overloads and ensure seamless recovery. Simulation results are validated through experimental testing.

The utilization of Direct Current (DC) railway systems is increasingly prevalent, as it constitutes the majority of urban tram power supply systems. Despite their high efficiency, the risk of ground faults is ever-present due to environmental issues and aging of the catenaries. These faults can interrupt the service for hours until repaired, requiring quick repair. To address this issue, this paper introduces a ground fault location method for catenaries in DC railway systems, based on the measurement of the DC voltage and ground current at each DC Traction Substation (TS). Then, the normalized ground currents relative to the overall fault current are compared with a model-based data pool, enabling the method to locate the fault along the protected catenary. The method's validity has been confirmed through numerous simulations and experimental tests. Initially, simulations were conducted on a three-TS DC railway model in Matlab-Simulink, yielding promising results. Subsequently, experimental laboratory tests were performed using uncontrolled rectifiers in the TS, also producing encouraging results. Finally, the suitability of the fault location method was verified using Hardware-In-the-Loop (HIL) tests emulating controlled rectifiers.

The integration of inverter-based resources (IBRs) is reshaping power grid operation by reducing system inertia, which impacts small-signal rotor angle stability and increases low-frequency oscillations (LFOs). While power-electronics-based flexible AC transmission systems (FACTSs) have been the primary solution, the shift of IBR control toward grid forming (GFM) is changing this approach. GFM control inherently provides inertia and affects small-signal stability, but implementing power oscillation damping (POD) algorithms in these inverters presents challenges, particularly regarding active-power-based ones (POD-P). Although various POD-P solutions are emerging for GFM inverters, few studies have evaluated their impact on the GFM device itself and their inherent capabilities, such as inertia and damping. This paper proposes that any design methodology should consider, besides the impact of POD controls on the grid, their effect on the properties of GFM devices. It introduces a theoretical framework using the network frequency perturbation (NFP) approach to assess this impact. Additionally, a simple POD-P control method is proposed for GFM controllers, with simplicity as its key advantage. The desired damping effect, along with the absence of impact on other frequency components, is verified through NFP analysis. The theoretical findings are experimentally validated with test bench results.

Utility-scale battery energy storage systems (BESS) are currently being used to provide auxiliary services, such as frequency regulation, peak shaving or grid balancing, among others. Hybrid ac/dc distribution grids where the BESS systems are connected in the dc side and the dc/ac interface is implemented through a grid forming (GF) converter are currently researched. These solutions combine the benefits given by the dc distribution and the possibility to provide emulated inertia and damping to the system through the use of GF control techniques. This article presents a novel tuning method, based on small signal analysis, for the configuration parameters of a dual-side GF controller. It aims to minimize the dynamic performance difference between the dual-side and ideal GF controllers, thus ensuring that the dual-side GF provides the expected support to the grid in terms of inertia, damping and primary response, while simultaneously controlling the dc voltage. This is achieved through the optimum tuning of the supplementary dc voltage regulator embedded in the dualside GF controller. Real-time estimation of the optimum controller gains by making use of an artificial neural network (ANN) is proposed. Simulation and experimental results are presented to validate the method.

The increasing penetration of power electronic converters into the grid demands advanced control strategies that ensure a high performance and stability, while avoiding undesired interactions with other grid components. Designing these converter controllers with traditional methods is becoming impractical, caused by the difficulties to simultaneously consider and balance diverse and conflicting objectives and to concurrently evaluate converter- and system-level objectives. This paper presents a multi-objective optimization (MOO) methodology aimed at multi-converter scenarios, which employs symbolic state-space representations to systematically explore optimal configurations across diverse performance measures. The methodology is first validated experimentally on a current-controlled grid-connected inverter, demonstrating that the objectives are handled better than with a conventional tuning approach. Additionally, the methodology is applied to a CIGRE benchmark system and compared to a traditional control tuning method to show the potential applications at more complex scenarios. The results demonstrate that the proposed MOO methodology effectively considers multiple converter- and system-level performance criteria simultaneously, leading to configurations that outperform the solutions obtained with conventional approaches.

Grid forming inverters are a promising technology to ensure the stability of weak grids. One typical strategy is the virtual synchronous generator (VSG) approach, which mimics the swing equation of synchronous generators. This strategy can provide inertia, primary frequency regulation and damping to the grid. However, in classical VSG structures, these three characteristics cannot be managed independently, and damping is usually limited. This work proposes a modified VSG controller, which adds a derivative term in the active power feedback, in order to provide an extra degree of freedom. This strategy enables the independent control of frequency services: damping, frequency regulation and inertia. Moreover, as the damping is affected by the impedance of the grid, an adaptive control strategy is proposed. By estimating the grid reactance and adapting the derivative term, the controller can ensure the desired damping along all operational conditions.