Abstract
The European Union (EU) energy strategy towards decarbonization led EU countries to elaborate their corresponding National Energy and Climate Plans (NECP) for the period 2021 to 2030. This paper analyzes the Portuguese and Spanish NECPs concerning their power systems. CEVESA, a model for the long-term planning and operation of the Iberian electricity system, is used. The analysis is based on simulating the reference NECP scenario, as well as other alternative scenarios with different solar and wind generation shares, CO2 prices and fuel costs. Results provide insights on the MIBEL electricity market evolution under the current decarbonization national strategies. © 2020 IEEE.

Abstract
Feed in generation was introduced in Portugal in 1988 to induce investments in endogenous and renewable energy resources. The feed in mechanism was adapted along time and its application was very successful so that currently more than 40% of the installed capacity is under this regime. Typically feed in tariffs are larger than average market prices so that there is a recurrent debate on whether this regime is pressing or not the end-user tariffs. This paper reports the main results obtained by the first author in his MSc Thesis in assessing the total generation cost under the current legal provisions on one side and, on the other, eliminating feed in generation from the mix. The results obtained using public data for 2017 indicate that the generation cost with feed in generation is 2,70% larger than the value obtained if it was eliminated from the market clearing process. © 2020 IEEE.

Abstract
This paper presents the results of an Agent-Based Model developed to simulate the Iberian Electricity Market, with special focus on the modelling of hydro power plants. To simulate the agent's dynamics in the day-ahead market, it was developed a bidding strategy based on a Q-Learning procedure. In the computation area, the recent years brought the discussion around artificial intelligence to a new upper level to complement traditional models, driven by the increased hardware computer capabilities, as well as new developments in the machine learning area. Reinforcement Learning models, as Q-Learning, are being widely used to represent complex systems such as electricity markets. The developed model is designed to simulate in a detailed way the hydro units that have a large impact in the electricity market common to Portugal and Spain. Apart from describing the developed model, this paper also includes results from its application to the Iberian Market case along 2018. © 2020 IEEE.

Abstract
Around the world, there is a great concern with the emission of greenhouse gases, creating great interest in turning the energy systems more sustainable. Multi-energy systems are considered as a potential solution to help to this cause and in recent years, it has gained much attention from both research and industry. In this paper, an optimization model is proposed to use the flexibility of multi-energy systems to mitigate the uncertainty associated with wind generation. The differences between the flexibility provided by multi-energy systems and electrical storage systems in the network were studied. The results prove that the flexibility of the multi-energy systems can benefit the system in several aspects and provide insights on which is the best approach to take full advantage of renewable resources even when a high degree of uncertainty is present.

Abstract
This paper proposes a "grey-box" aggregated dynamic model for active distribution networks, taking into account a heterogeneous fleet of generation technologies alongside their expected behavior when taking into account the latest European grid codes requirements in terms of voltage support services. The main goal of the proposed model and underlying methodology for its identification is to represent the transient behavior of the active distribution system following large voltage disturbances occurring at the transmission side. The proposed aggregated model is composed by three main components: an equivalent power converter for generation and battery energy storage systems portfolio representation; an equivalent synchronous generation unit; and an equivalent composite load model. The model's parameters are estimated by an evolutionary particle swarm optimization algorithm, by comparing a fully-detailed model of a distribution network with the aggregated model's frequency domain's responses of active and reactive power flows, at the boundary of transmission-distribution interface substation.

Abstract
This study presents a conceptual model addressing the establishment of connection requirements for power-converter-interfaced renewable generation in islanded power systems. The replacement of fossil-fuel generation by time-variable renewable sources implies important changes in the system operation philosophy with respect the dynamic security resulting from the proliferation of power electronic interfaced units and reduction of regulation capacity existing in conventional units. Taking into consideration such an environment, this work focuses on the Madeira Island study case, which is facing a tremendous challenge regarding medium-term plans for renewables integration that lead to operational scenarios with 100% of power infeed from renewables in a system characterised by a diversity of resources. The requirements for the future renewable generation systems were identified via extensive dynamic simulations of large disturbances performed in those operating scenarios.