Abstract
Renewable energy-based microgrids (MGs) strongly depend on the implementation of energy storage technologies to optimize their functionality. Traditionally, electrochemical batteries have been the predominant means of energy storage. However, technological advancements have led to the recognition of hydrogen as a promising solution to address the long-term energy requirements of microgrid systems. This study conducted a comprehensive literature review aimed at analysing and synthesizing the principal optimization and control methodologies employed in hydrogen-based microgrids within the context of building microgrid infrastructures. A comparative assessment was conducted to evaluate the merits and disadvantages of the different approaches. The optimization techniques for energy management are categorized based on their predictability, deployment feasibility, and computational complexity. In addition, the proposed ranking system facilitates an understanding of its suitability for diverse applications. This review encompasses deterministic, stochastic, and cutting-edge methodologies, such as machine learning-based approaches, and compares and discusses their respective merits. The key outcome of this research is the classification of various energy management strategy methodologies for hydrogen-based MG, along with a mechanism to identify which methodologies will be suitable under what conditions. Finally, a detailed examination of the advantages and disadvantages of various strategies for controlling and optimizing hybrid microgrid systems with an emphasis on hydrogen utilization is provided.

Abstract
Reliability analysis of large power networks requires accurate aggregate models of low voltage (LV) networks to allow for reasonable calculation complexity and to prevent long computational times. However, commonly used lumped load models neglect the differences in spatial distribution of demand, type of phase-connection of served customers and implemented protection system components (e.g., single-pole vs three-pole). This paper proposes a novel use of state enumeration (SE) and Monte Carlo simulation (MCS) techniques to formulate more accurate LV network reliability equivalents. The combined SE and MCS method is illustrated using a generic suburban LV test network, which is realistically represented by a reduced number of system states. This approach allows for a much faster and more accurate reliability assessments, where further reduction of system states results in a single-component equivalent reliability model with the same unavailability as the original LV network. Both mean values and probability distributions of standard reliability indices are calculated, where errors associated with the use of single-line models, as opposed to more detailed three-phase models, are quantified.

Abstract
The 2025 blackout across the Iberian Peninsula marked a paradigm shift in the nature of power system failures, revealing how modern grids-dense with inverter-based resources and automated controls-can exhibit emergent instabilities that traditional design frameworks may not fully anticipate. This review examines the event through the lens of complex systems engineering, drawing on publicly available information and prior research to illustrate why a well-instrumented, high-renewables grid might still struggle to contain rapidly evolving disturbances. We begin by highlighting structural features-such as bottlenecks and asymmetric interconnections-that have been shown in the literature to influence the propagation of instability in transmission networks. Network-science tools, including algebraic connectivity, spectral radius and betweenness centrality, are discussed as methods used in previous studies to reveal latent fragilities. Attention then shifts to synchronization dynamics, where low-inertia conditions can amplify frequency deviations and interact with heterogeneous inverter response characteristics. Using models of cascading failures and percolation-type transitions, we outline how disruptions can propagate nonlocally, highlighting mechanisms identified in analytical and simulation studies. The analysis extends to fragility scoring systems, modular segmentation strategies and the spatial deployment of virtual inertia and fast-response resources-approaches proposed in prior research as part of a resilience toolkit aimed at containment and stabilization. Finally, we summarize emerging redesign directions emphasizing harmonized protection logic, regional operational cells and complexity-aware digital twins as increasingly important under conditions of uncertainty.