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 replacement of fossil fuel power plants by variable renewable energy sources is reducing the flexibility of the energy system, which puts at risk its security. Exploiting the flexibility of distributed multi-energy resources through aggregators presents a solution for this problem. In this context, this paper presents a new hierarchical model predictive control framework to assist multi-energy aggregators in the network-secure delivery of multi-energy services traded in electricity, natural gas, green hydrogen, and carbon markets. This work builds upon and complements a previous work from the same authors related to bidding strategies for day-ahead markets - it closes the cycle of aggregators' participation in multi-energy markets, i.e., day-ahead bidding and real-time activation of flexibility services. This new model predictive control framework uses the alternating direction method of multipliers on a rolling horizon to negotiate the network-secure delivery of multi-energy services between aggregators and distribution system operators of electricity, gas, and heat networks. We used the new model predictive control framework to conduct two studies. In the first study, we found that considering multi-energy network constraints at both day-ahead and real-time optimization stages produces the most cost-effective and reliable solution to aggregators, outperforming state-of-the-art approaches in terms of cost and network security. In the second study, we found that the adoption of a green hydrogen policy by multi-energy aggregators can reduce their consumption of natural gas and respective CO2 emissions significantly if carbon and green hydrogen prices are competitive.& COPY; 2023 Elsevier Ltd. All rights reserved.

Abstract
The decarbonization of the economy and the increasing integration of renewable energy sources into the generation mix are bringing new challenges, requiring novel technological solutions in the topic of smart grids, which include smart transformers and energy storage systems. Additionally, power quality is a vital concern for the future smart grids; therefore, the continuous development of power electronics solutions to overcome power quality problems is of the utmost importance. In this context, this article proposes a novel three-phase multiobjective unified power quality conditioner (MO-UPQC), considering interfaces for solar PV panels and for energy storage in batteries. The MO-UPQC is capable of compensating power quality problems in the voltages (at the load side) and in the currents (at the power grid side), while it enables injecting power into the grid (from the PV panels or batteries) or charging the batteries (from the PV panels or from the grid). Experimental results were obtained with a three-phase four-wire laboratory prototype, demonstrating the feasibility and the large range of applications of the proposed MO-UPQC.

Abstract
In isolated power systems with very high instantaneous shares of renewables, additional inertia should be used as a complementary resource to battery energy storage systems (BESSs) for improving frequency stability, which can be provided by synchronous condensers (SCs) integrated into the system. Therefore, this paper presents a methodology to infer the system dynamic security, with respect to key frequency indicators, following critical disturbances. Of particular interest is the evidence that multiple short-circuit locations should be considered as reference disturbances regarding the frequency stability in isolated power grids with high shares of renewables. Thus, an artificial neural network (ANN) structure was developed, aiming to predict the network frequency nadir and Rate of Change of Frequency (RoCoF), considering a certain operating scenario and disturbances. For the operating conditions where the system frequency indicators are violated, a methodology is proposed based on a gradient descent technique, which quantifies the minimum amount of additional synchronous inertia (SCs which need to be dispatch) that moves the system towards its dynamic security region, exploiting the trained ANN, and computing the sensitivity of its outputs with respect to the input defining the SC inertia.