Hydrogen electrloyzers are power-to-gas storage devices that can facilitate large-scale integration of intermittent renewable sources into the future power systems. Due to their fast response and capability to operate in different loading conditions, they can be used as responsive loads providing support to AC grid during transients. This paper suggests taking one step further and using hydrogen electrolyzers to provide grid-forming services to the grid. As a result, the electrolyzer's role is elevated from supporting the grid (responsive load) to actively participating in forming voltage and frequency of the grid. The grid-forming capability of electrolyzer is linked to its hydrogen production constraints, which can potentially pose limitations on the grid-forming services. Besides the grid-forming mode, two additional operating modes, i.e., DC voltage mode and constant power mode, are proposed to ensure a safe operation of the electrolyzer in case of adversary interaction between grid-forming operation and hydrogen production constraints. This paper also studies the impacts of grid-forming services on the electrolyzer's physical features such as hydrogen stack temperature and efficiency. Comprehensive simulations are conducted on a low-inertia test network whose topology is inspired by a portion of the transmission grid in South Australia to confirm the effectiveness of the proposed concept under various operational conditions of the electrolyzer and upstream AC grid. Moreover, the practical feasibility of the proposed control system is experimentally validated by conducting hardware-in-the-loop tests.

The development of multiterminal VSC-HVDC grids poses a new challenge: a fast and selective protection algorithm for such grids needs to be implemented. Therefore, this paper addresses a novel protection algorithm, which proves to be accurate, fast and selective for various combinations of fault distance, impedance and power flow scenarios in a multiterminal VSC-HVDC environment. It relies on the wavelet transform and principal component analysis to retrieve information from the local DC current measurement, generating a highly informative input for a genetic fuzzy system. Based on previously simulated fault scenarios, the genetic fuzzy system is able to decide if the input signal refers to an internal or external fault, generating the trip signal when needed. Furthermore, the method has the advantage of using local measurements to avoid communication delay. Finally, the algorithm was implemented in hardware and tested in a hardware-in-the-loop simulation, which emphasizes the practical use of the proposed protection scheme.

A microgrid (MG) is part of a distribution system that comprises loads and distributed energy resources, capable of operating either connected to or islanded from the primary grid. Having an appropriate design, MG controllers improve energy efficiency, playing a vital role in the modern distribution system. Thus, MG management and control has become a broad area of research due to its complex operation. Reinforcement learning (RL) offers adaptive solutions for handlingMGcomplex dynamics and nonlinearity. It is an alternative to traditional algorithms and control methods in tasks such as load frequency control, resource allocation, and energy management. Due to the relevance of the topic, this survey examined the role of RL in MG control and management, offering a comprehensive update on previous reviews, categorising articles by RL type, control objectives, and MG operational modes. Additionally, hardware implementations and performance assessments across RL-based solutions were evaluated. The present survey identified key research trends and gaps, contributing to understanding the role of RL in MG management and control and guiding future solutions in the field.

High Impedance Faults (HIFs) occur by the contact between an energized conductor and a high impedance surface. Due to the low fault current level, HIFs cannot be detected by conventional protection and there is no fully efficient solution to this problem. HIF detection methods often extract metrics using signal processing techniques, such as Fourier Transform, Wavelet Transform, Stockwell Transform, and Mathematical Morphology. However, these techniques are applied under specific conditions, which hinders comparative and critical analyses among them. Therefore, this paper presents a critical review of HIF detection methods based on the aforementioned techniques, and also shows a detailed investigation of the performance of the metrics commonly used with them. To do this efficiently, the authors proposed a set of assessment indices based on the ratio between the metrics’ characteristics and another one based on the repeating of the metrics features. The proposed indices revealed that some of these metrics fail to distinguish HIF from other typical occurrences in power distribution systems, and their performances are negatively affected by the fault location and by the existence of noise in the measurements. Additionally, the results showed a need to specify system conditions in which any HIF detection technique is valid.

Modern power systems are facing the tremendous challenge of integrating vast amounts of variable (non-dispatchable) renewable generation capacity, such as solar photovoltaic or wind power. In this context, the required power system flexibility needs to be allocated in other units that can include energy storage, demand management or providing reserve from renewables curtailing the output power. The present paper proposes the new concept of grid-forming load, which can be considered a totally flexible concept of demand. The concept is not only ensuring the load is supporting the grid stability by adapting the load to the overall system balancing, but also ensures that the load is actually contributing to form the grid and to provide synchronization power to the overall system. In this sense, the new concept allows running a system powered only by renewables operating at maximum power (or operator defined set-point) in grid-following mode, while the overall system control is ubicated in the demand side. This is an important change of paradigm as it considers that all the flexibility, synchronism and stability provision is on the demand side. This concept can applied either to isolated systems or also to future power systems, where millions of loads steer the power system while the renewables are operating at full power. The paper proposes the concept, suggests possible control implementations of the grid-forming load and analyses the concept in four simulation case studies.

With the large integration of converter-interfaced generation (CIG) and widespread of power electronic interfaced technologies, power system dynamic behaviour is becoming progressively faster. As a consequence, is often unclear when to use EMT or Phasor models in grid integration studies. Therefore, this paper presents useful simulation guidelines of Voltage-Source Converters (VSCs) used in AC grid integration studies. It also presents several EMT and Phasor models suited to simulate CIG and renewable energy resources connected to power systems. Several modelling approaches and suitability analyses were provided based on a comprehensive comparative study among the models. Various studies were performed in a small system, composed of two generators, and a CIGRE benchmark system, both modelled in Simulink. We address a gap related to the suitability of CIGs phasor models in studies where the boundary between electromagnetic and electromechanical transients overlap. An insightful analysis of the adequate simulation time step for each model and study is also provided.