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.

Abstract
Transmission Expansion Planning (TEP) aims at identifying a list of new assets to be installed on the transmission grid to meet the long-term forecasted demand while ensuring a safe supply over the entire planning horizon. As TEP is a Mixed Integer Non-Linear Problem (MINLP) with a huge search space, in the last years several modern heuristic algorithms were proposed to deal with its challenging characteristics. In this way, this paper describes and evaluates the impact and implementation of four operators that can be easily incorporated in any evolutionary algorithm, namely: Neighborhood Search for Local Improvement (NSLI), Diversity Control (DC), Elitist Reproduction (ER) and Boundary Local Search (BLS). The impact of these operators is assessed and discussed over a hundred simulations using a traditional Genetic Algorithm (GA) and a well-known test system, the RTS 24-bus. Regarding the results, the NSLI and the BLS operator considerably improved the GA performance in solving the TEP problem regarding both the final value of the objective function and the diversity of solutions.

Abstract
This paper presents a heuristic algorithm to reduce the set of equipment candidates for Transmission Expansion Planning (TEP). Since it is a Constructive Heuristic Algorithm (CHA), the MiniEff algorithm aims at reducing the computational burden involved in the optimization process in a quick and satisfactory way. This approach includes two major blocks. The first one uses the minimum-effort calculation based on DC-OPF analysis to reduce the search space of the TEP problem. Then, the reduced list of investment alternatives is input to the AC-TEP formulation to build the final expansion plan using the Evolutionary Particle Swarm Optimization technique (EPSO). The tests on the developed TEP approach were done using the IEEE 118 Bus System and they demonstrate the gains that were obtained in terms of reducing the computer burden in solving TEP without compromising the quality of the final plans.

Abstract
In the last two decades, power systems have experienced several changes, mainly related to organizational and operational restructuring. The appearance of new actors contributes to developing new business models and modifies its traditional operation activities. As a direct result, there is a need for new control solutions and strategies to integrate these different players. Agent-Based Models (ABM) have been increasingly used to model complex systems since they are especially suited to model systems influenced by social interactions between flexible, autonomous, and proactive agents. This paper provides a review of the literature regarding ABM in power systems followed by an analysis in more detail regarding specific applications that are becoming relevant in this new paradigm.