Abstract
With the expansion of power electronics possibilities for smart homes, new perceptions for power control are emerging, suggesting new possibilities also for smart grids. In this prospect, the solid-state transformer (SST) has a substantial impact to interface smart homes with smart grids, guaranteeing high levels of power quality in both grid (consumed current) and load side (produced voltage). Nevertheless, as advanced contributions, the SST can deal with other possibilities of controllability. In such situation, an analysis of new operation opportunities for the SST into smart homes and smart grid perspectives is offered in this paper. It is discussed the SST principle of operation, with a thorough clarification concerning the proposed control algorithms, as well as an intuitive computational validation contemplating contingencies of operation about power quality effects for the load and grid side. The attained results strengthen the attractiveness of the new operation opportunities for the SST when utilized as interface between homes and smart grids.

Abstract
This paper investigates the contribution of hydrogen electrolysers (HEs) as highly controllable loads in the context of the Frequency Containment Reserve (FCR), in future operation scenarios on the Iberian Peninsula (IP). The research question is whether HEs can mitigate system insecurity regarding frequency or Rate of Change of Frequency (RoCoF) in critical periods of high renewable energy penetration (i.e. low system inertia), due to the fact that these periods will coincide with high volume of green hydrogen production. The proposed simulation platform for analysis consists of a simplified dynamic model developed in MATLAB/Simulink. The results obtained illustrate how HEs can outperform conventional generators on the provision of FCR. It is seen that the reference incident of 1GW loss in the IP in a 2040 low inertia scenario does not lead to insecure values of either frequency or Rate of Change of Frequency (RoCoF). On the other hand, an instantaneous loss of inverter-based resources (IBR) generation following a short-circuit may result in RoCoF violating security thresholds. The obtained results suggest that the HEs expected to be installed in the IP in 2040 may contribute to reduce RoCoF in this case, although this mitigation may be insufficient. The existing FCR mechanism does not fully exploit the fast-ramping capability of HEs; reducing measurement acquisiton delay would not improve results.

Abstract
Minimising the total power losses and enhancing the voltage profile is achieved using a proposed multi-objective chaotic salp swarm algorithm with fuzzy logic decision-making. The proposed multi-objective chaotic salp swarm algorithm is utilised to determine the optimal size and location of photovoltaic in radial distribution system to minimise the total power losses, total voltage deviation, and maximise the voltage stability index. In addition, the proposed multi-objective chaotic salp swarm algorithm is used to find suitable scheduling for battery energy storage charge/discharge during 24 h considering the intermittent nature of photovoltaic power generation. The proposed algorithm is tested on standard and practical radial distribution systems (IEEE 33-bus and 94-bus Portuguese systems). The performance of the proposed algorithm is validated by comparing its results with those obtained by other competitive optimisation techniques. The obtained results prove the ability of the proposed algorithm to achieve an efficient setting for photovoltaics and battery energy storages and determine their optimal allocations in order to minimise the power losses and enhance the voltage profile with satisfying all operating constraints.

Abstract
The rapid expansion of offshore wind farms and the development of energy islands for green hydrogen production have introduced futuristic off-grid systems. These systems can experience total shutdowns, necessitating black start solutions to ensure reliable restoration capabilities for isolated offshore wind farms. This paper investigates a grid-forming converter sizing strategy to enable black start capabilities in off-grid offshore wind farms. The study evaluates the impact of different energization strategies on battery energy storage system (BESS) sizing, focusing on soft energization with droop control in wind turbines and electrolyzers, the effects of wind turbine ramp rates on BESS requirements, and the role of switchable shunt reactors at the offshore substation for reactive power management. A comparative analysis is conducted between soft + hard and pure soft energization sequences to assess their impact on BESS converter sizing. Results demonstrate that the combined soft + hard energization strategy significantly reduces BESS converter size, offering a more cost-effective black start solution compared to pure soft energization.

Abstract
Maintaining frequency stability is one of the biggest challenges facing future power systems, due to the increasing penetration levels of inverter-based renewable resources. This investigation experimentally validates the frequency provision capabilities of a real Polymer Electrolyte Membrane (PEM) hydrogen electrolyser (HE) using a power hardware-in-the-loop (PHIL) setup. The PHIL consists of a custom 3-level interleaved buck converter and a hardware platform for real-time control of the converter and conducting grid simulation, associated with the modelling of the future Iberian Peninsula (IP) and Continental Europe (CE) systems. The investigation had the aim of validating earlier simulation work and testing new responses from the electrolyser when providing different frequency services at different provision volumes. The experimental results corroborate earlier simulation results and capture extra electrolyser dynamics as the double-layer capacitance effect, which was absent in the simulations. Frequency Containment Reserve (FCR) and Fast Frequency Response (FFR) were provided successfully from the HE at different provision percentages, enhancing the nadir and the rate of change of frequency (RoCoF) in the power system when facing a large disturbance compared to conventional support only. The results verify that HE can surely contribute to frequency services, paving the way for future grid support studies beyond simulations.

Abstract
In a high-risk sector, such as power system, transparency and interpretability are key principles for effectively deploying artificial intelligence (AI) in control rooms. Therefore, this paper proposes a novel methodology, the evolving symbolic model (ESM), which is dedicated to generating highly interpretable data-driven models for dynamic security assessment (DSA), namely in system security classification (SC) and the definition of preventive control actions. The ESM uses simulated annealing for a data-driven evolution of a symbolic model template, enabling different cooperative learning schemes between humans and AI. The Madeira Island power system is used to validate the application of the ESM for DSA. The results show that the ESM has a classification accuracy comparable to pruned decision trees (DTs) while boasting higher global inter-pretability. Moreover, the ESM outperforms an operator-defined expert system and an artificial neural network in defining preventive control actions.