Abstract
Electrical utilities apply condition monitoring on power transformers (PTs) to prevent unplanned outages and detect incipient faults. This monitoring is often done using dissolved gas analysis (DGA) coupled with engineering methods to interpret the data, however the obtained results lack accuracy and reproducibility. In order to improve accuracy, various advanced analytical methods have been proposed in the literature. Nonetheless, these methods are often hard to interpret by the decision-maker and require a substantial amount of failure records to be trained. In the context of the PTs, failure data quality is recurrently questionable, and failure records are scarce when compared to nonfailure records. This work tackles these challenges by proposing a novel unsupervised methodology for diagnosing PT condition. Differently from the supervised approaches in the literature, our method does not require the labeling of DGA records and incorporates a visual representation of the results in a 2D scatter plot to assist in interpretation. A modified clustering technique is used to classify the condition of different PTs using historical DGA data. Finally, well-known engineering methods are applied to interpret each of the obtained clusters. The approach was validated using data from two different real-world data sets provided by a generation company and a distribution system operator. The results highlight the advantages of the proposed approach and outperformed engineering methods (from IEC and IEEE standards) and companies legacy method. The approach was also validated on the public IEC TC10 database, showing the capability to achieve comparable accuracy with supervised learning methods from the literature. As a result of the methodology performance, both companies are currently using it in their daily DGA diagnosis.

Abstract
The power distribution grid is centrally managed concerning the requirements of the end-users, however, with the appearance of smart grids, new technologies arc arising. Therefore, distributed energy resources, mainly, renewables, energy storage systems, electric mobility, and power quality are viewed as encouraging contributions for improving power management. In these circumstances, this paper presents a power electronics perspective for the power distribution grid, considering innovative features, and including a power quality perception. Throughout the paper are presented relevant concepts for a concrete realization of a smart grid, supported by the integration of power electronics devices as the interface of the mentioned technologies. Aiming to support the innovative power electronics systems for interfacing the mentioned technologies in smart grids, a set of developed power electronics equipment was developed and, along with the paper, are shown and described, supporting the most important contributions of this paper.

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
Due to the complexity and great relevance of the transmission network expansion planning (TNEP) for electrical systems, this topic remains on the focus of the academic and industry communities. Therefore, this paper proposes a new approach to deal efficiently with the basic formulation of this problem, combining low computational effort and good quality of the obtained solutions. In this approach four factors contribute to solve TNEP problem more efficiently: (i) the investment decisions are selected using a new Constructive Heuristic Algorithm (CHA); (ii) the proposed CHA includes two stages, using the relaxation of the decision integers variables through the hyperbolic tangent function and the setting of its function's slope; (iii) the performance index that was adopted was modified regarding what was reported in the literature; (iv) the use of the primal-dual interior point optimization technique allows the representation of the nonlinearities in the problem: transmission power losses and the hyperbolic tangent function (investment decision). The quality and effectiveness of the proposed algorithm is verified using two real power systems, where the proposed CHA is able to lead to better quality solutions than the ones reported in the literature.

Abstract
The green hydrogen (H-2) technology has an important role to play in the European Union energy strategy towards decarbonization. Apart from traditional H-2 industrial usages, there is an increasing attention to its use in the heavy transport sector, in other energy-intensive industries, and in heating applications. Green H-2 production is planned to be based on renewable electricity generation and its production at an industrial scale may have a significant impact on the electricity markets. This research assesses the electricity cost of producing H-2 and its impact on the Iberian electricity market. Different evolution scenarios including a partially flexible H-2 demand, based on the Spanish and Portuguese energy and climate plans, have been considered for this assessment.

Abstract
Energy communities and self-consumption are considered as major drivers to achieve the decarbonization of the power sector, contributing to further increase the penetration of renewables, and empowering end consumers by turning them more active and flexible regarding electricity consumption. Considering the relevance of this topic and given that the corresponding legislation is recent, this paper summarizes the European Regulation on self-consumption and renewable energy communities and describes, analyses and compares its transposition to the Portuguese and Spanish national regulations. The main regulatory barriers for renewable energy communities' rollout are identified and regulatory improvements are proposed to overcome them.