The growing integration of renewable-based distributed energy resources within local energy communities is significantly reshaping the operational dynamics of medium voltage distribution networks, particularly affecting their reliability and protection schemes. This work investigates the technical impacts of the high penetration of distributed generation within sustainable local energy communities on the effectiveness of fault detection, location, isolation, and service restoration processes, from the point of view of Distribution System Operators. From a supply continuity perspective, the methodology of the present work comprises a comprehensive, quantitative, system-level assessment based on probabilistic, scenario-based simulations of fault events on a CIGRE benchmark distribution network. The models incorporate component fault rates and repair times derived from EPRI databases and compute standard IEEE indices over a one-year horizon, considering manual, hybrid, and fully automated operation scenarios. The results highlight the significant potential of automation to enhance supply continuity. However, the qualitative assessment carried out through laboratory-based Hardware-in-the-Loop tests reveals critical vulnerabilities in fault-detection devices, particularly when inverter-based distributed generation units contribute to fault currents. Consequently, quantitative evaluations based on a sensitivity analysis incorporating these findings, varying the reliability of fault-detection systems, indicate that the reliability improvements expected from increased automation levels are significantly deteriorated if protection malfunctions occur due to fault current contributions from distributed generation. These results underscore the need for the evolution of protection technologies in medium voltage networks to ensure reliability under future scenarios characterised by high shares of distributed energy resources and local energy communities.

The undergoing energy transition to a sustainable future requires, among other things, the application of demand side management (DSM) techniques to maintain grid stability and allow a smooth performance. To successfully implement DSM strategies, near real-time monitoring of the grid is required. This can be achieved through a distribution system state estimator (DSSE). Conventional approaches to state estimation (SE) typically rely on the assumption of a balanced reference bus, which is reasonable for transmission systems but may not be applicable to low-voltage distribution networks, even more with significant distributed generation (DG) penetration. To address this problem, a branch current-based low-voltage DSSE for unbalanced three-phase systems is developed. The algorithm incorporates a virtual bus to account for highly unbalanced systems, enabling it to obtain a more accurate estimation of the grid state. The proposed method is compared to the conventional balanced reference bus method through multiple simulations under different load conditions in the IEEE European low-voltage test feeder.

The growing integration of distributed energy resources and electrification of end users is driving the need for greater system flexibility in modern power grids. Various electrical assets can contribute to this flexibility, either inherently or through external control mechanisms, although their suitability varies even within the same category of assets. This paper presents a novel methodological approach to assess the flexibility potential of electrical assets based on their inherent technical characteristics and their intended installation context. Inspired by the principles of the Smart Readiness Indicator (SRI) for buildings, the proposed method employs a scoring system to evaluate a set of key functionalities that determine an asset’s readiness to contribute to system flexibility, then through a weighted sum a final index is obtained. These scores are combined through a weighted aggregation to produce a single, easy-to-interpret index that synthesizes multiple characteristics, enabling comparisons across different technologies. Unlike the SRI, this approach is not focused on certification but rather on providing a decision-support tool for end-users. The applicability of the method is demonstrated through a case study evaluating a photovoltaic inverter, followed by a sensitivity analysis to assess the robustness of the weighting scheme. Results indicate that the proposed index provides a transparent and replicable means of quantifying flexibility potential, supporting more informed planning and investment decisions.