Abstract
The present work aims to compare several load disaggregation methods. While the supervised alternative was found to be the most competent, the semi-supervised is proved to be close in terms of potential, while the unsupervised alternative seems insufficient. By the same token, the tests with long-lasting data prove beneficial to confirm the long-term performance since no significant loss of performance is noticed with the scalar of the time-horizon. Finally, the patchwork of new parametrization and methodology fine-tuning also proves interesting for improving global performance in several methods.

Abstract
In Europe, clean distributed generation, DG, is perceived as a crucial instrument to build the path towards carbon emission neutrality. DG already reached a large share in the generation mix of several countries and the reduction of technical losses is one of its most mentioned advantages. In this scope, this paper discusses the weaknesses of this postulation using real networks. The adopted methodology involves the power flow simulation of a collection of real networks, using 15 min real measurements of loads and generations for a whole year. The clustering of similar cases allows identifying the situations that cause higher losses. A complementary objective of this research was to define an approach to mitigate this problem in terms of identifying the branches that, if reinforced, most contribute to losses reduction. The results obtained confirm the rationality of the proposed methodology.

Abstract
The financial planning of distribution systems usually includes the prediction of annual mandatory investments, concerning the resources that the DSO is compelled to allocate as a result of new network connections, required by new consumers or new energy producers. This paper presents a methodology to estimate the mandatory investments that the DSO should do in the distribution network. These estimations are based on historical data, load growth expectations and various socioeconomic indices. However, the available database contains very few annual investment examples (one aggregated value per year since 2002) compared to the large number of variables (potential inputs), which is a factor of regression overfitting. Thus, the applicable regression techniques are restrained to simple but efficient models. This paper describes a new methodology to identify the most suitable estimation models. The implemented application automatically builds, selects, and tests estimation models resulting from combinations of input variables. The final forecast is provided by a committee of models. Results obtained so far confirm the feasibility of the adopted methodology.

Abstract
Recent advances in electric vehicle (EV) charging capability have seen a wide growth in the consumer market, which will continue to increase in future years with favourable policy incentives. However, the uncontrolled connection and charging of EV may have an adverse effect on three-phase distribution grids operation. This paper presents the impact of EV integration in a real LV Portuguese urban network. It analyses the network loading, energy losses, and voltage imbalances, under different scenarios of EV charging location and phase connection. The DIgSILENT Power Factory software is used in the voltage imbalance studies. Preliminary results show that the voltage drop in the analysed network is significantly affected by the location of the EV. Furthermore, as expected, the unbalanced EV loading leads to an increase of voltage unbalance between phases which is more pronounced when higher levels of EV are considered. © 2021 The Institution of Engineering and Technology.

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.