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Microgrids are considered a viable solution for achieving net-zero targets and increasing renewable energy integration. However, there is a lack of conceptual work focusing on practical data analytics deployment schemes and case-specific insights. This paper presents a scalable and flexible physical and digital architecture for extracting data-driven insights from microgrids, with a real-world microgrid utilized as a test-bed. The proposed architecture includes edge monitoring and intelligence, data-processing mechanisms, and edge–cloud communication. Cloud-hosted data analytics have been developed in AWS, considering market arrangements between the microgrid and the utility. The analysis involves time-series data processing, followed by the exploration of statistical relationships utilizing cloud-hosted tools. Insights from one year of operation highlight the potential for significant operational cost reduction through the real-time optimization and control of microgrid assets. By addressing the real-world applicability, end-to-end architectures, and extraction of case-specific insights, this work contributes to advancing microgrid design, operation, and adoption. [ABSTRACT FROM AUTHOR]

In recent decades, the rapid rise in electricity demand has compelled transmission and distribution systems to operate at almost their maximum capacity. This can pose numerous technical challenges such as excessive power losses, voltage and transient instabilities, as well as reduced power quality and reliability. Employment of Flexible Alternating Current Transmission System (FACTS) devices can be an effective approach to obviate such challenges and reinforce the power system functionality. Nevertheless, FACTS devices require a high initial investment, and hence their optimal allocation in terms of various aspects such as type, size and location is of utmost importance. This cannot be achieved without the deployment of optimization techniques. The aim of this paper is to provide a comprehensive review of the existing proposals for the enhancement of power system performance adopting FACTS devices. Adhering to that, an in-depth analysis is carried out, in which the most pertinent options are classified into specific groups based on their optimization objectives. Finally, a comparative analysis is accomplished in which the main attributes and drawbacks of each optimization technique are presented. [ABSTRACT FROM AUTHOR]

10.3390/en14051349 5 van der Blij N.H., Purgat P., Soeiro T.B., Ramirez-Elizondo L.M., Spaan M.T.J., Bauer P. Decentralized Plug-and-Play Protection Scheme for Low Voltage DC Grids. The electrical energy industry is undergoing dramatic changes; the massive deployment of renewables, an increasing share of DC networks at transmission and distribution levels, and at the same time, a continuing reduction in conventional synchronous generation, all contribute to a situation where a variety of technical and economic challenges emerge. As society's reliance on electrical power continues to increase as a result of international decarbonisation commitments, the need for the secure and uninterrupted delivery of electrical energy to all customers has never been greater. [Extracted from the article]

Electric Vehicles (EVs) are becoming increasingly available and are expected to be a large part of the load in future power systems. EV chargers are a relatively new type of load and are mainly interfaced with the grid through power electronics. It is therefore important to investigate the impact they have on power system dynamic behaviour. In this paper, two detailed EV charger models (representing a typical slow and fast charger) were investigated. The aim was to test the capability of standard static—and more importantly, dynamic—load models, commonly used in power system studies, to represent the static and dynamic behaviour of EV chargers. Different control parameter settings for two types of EV chargers were investigated, as were the limits of standard power system dynamic load model structures' accurate representation. Typical parameter sets have also been provided for cases where proper representation was possible. [ABSTRACT FROM AUTHOR]

With the high penetration of Renewable Energy Sources (RES) in power systems, the short-circuit levels have changed, creating the requirement for altering or upgrading the existing switchgear and protection schemes. In addition, the continuous increase in power (accounting both for generation and demand) has imposed, in some cases, the need for the reinforcement of existing power system assets such as feeders, transformers, and other substation equipment. To overcome these challenges, the development of superconducting devices with fault current limiting capabilities in power system applications has been proposed as a promising solution. This paper presents a power system fault analysis exercise in networks integrating Superconducting Cables (SCs). This studies utilized a validated model of SCs with second generation High Temperature Superconducting tapes (2G HTS tapes) and a parallel-connected copper stabilizer layer. The performance of the SCs during fault conditions has been tested in networks integrating both synchronous and converter-connected generation. During fault conditions, the utilization of the stabilizer layer provides an alternative path for transient fault currents, and therefore reduces heat generation and assists with the protection of the cable. The effect of the quenching phenomenon and the fault current limitation is analyzed from the perspective of both steady state and transient fault analysis. This paper also provides meaningful insights into SCs, with respect to fault current limiting features, and presents the challenges associated with the impact of SCs on power systems protection. [ABSTRACT FROM AUTHOR]