Abstract
As the global community transitions towards decarbonization and sustainable energy, green hydrogen is emerging as a key clean energy carrier. This paper addresses the role of hydrogen in transportation, emphasizing the European Union's additionality principle for renewable energy sources in green hydrogen production. It introduces a model for optimally designing hydrogen fueling stations, considering electrolyzers, hydrogen storage, fuel cells, PV systems, and batteries. This model also considers the participation in electricity (energy and secondary reserve), hydrogen, and oxygen markets, and it is evaluated under different additionality policy scenarios. Results indicate that stricter additionality policies reduce the internal rate of return. However, participation in secondary reserve markets significantly boosts operational revenues and compensates for higher investment costs.

Abstract
Frequency stability in inverter-based renewable energy sources (RES)-dominated, low-inertia, power systems is a timely challenge. This paper employs a systematic approach, utilizing an artificial neural network (ANN) and dynamic simulation, to infer two key frequency stability indicators: nadir and rate of change of frequency (RoCoF). By reformulating the ANN mathematical model, these indicators are then integrated as mixed-integer non-linear constraints into a classical AC security-constrained optimal power flow (AC SCOPF), resulting in the proposed AC-F-SCOPF problem. The results of the proposed AC-F-SCOPF on the IEEE 39-bus system show that the problem identifies accurately the synchronous condensers which must run to ensure the frequency stability.

Abstract
Traditionally, proportional-integral (PI) control has ensured the successful application of automatic generation control (AGC). Two design features of AGC-PI are the following: (1) it is merely a reactive system which does not take full advantage of existing knowledge about the system and (2) the control signal sent to all units is divided proportionally to their participation in the AGC. These two features ensure simplicity and, thus, reliability for the regular functioning of the power system. However, when the power system is recovering from a loss of generation, such features can become shortcomings. This paper proposes a model predictive control (MPC) to improve performance of AGC in such a scenario. The contrast with the traditional approach is as follows: instead of using merely two system measures which are also the control objectives (frequency and interconnection flow), the proposed controller relies on an internal model that takes advantage of further known variables of the power system, especifically the ramping capabilities of participating units. While still respecting the participation factors, it is shown that the proposed model allows to exhaust earlier the availability of faster units, such as some demand response, as the one to be provided by hydrogen electrolysers, and thus reestablishes the frequency and interconnection flows in a faster way than typical AGC-PI.

Abstract
This chapter presents key insights for the planning and operation of distribution power grids integrating high shares of renewable generation and charging capacity for electric vehicles (EVs). Case studies are presented to illustrate the impact of expected trends for vehicle electrification in the operation and future expansion of distribution power grids. The potential of innovative approaches is also exploited. The smart-transformer concept based on solid-state-transformer architectures as well as hybrid AC/DC distribution grids is qualitatively evaluated as a suitable solution for the massive integration of EV charging.

Abstract
This paper introduces a mathematical model designed to optimise the operation of natural gas distribution networks, considering the injection of hydrogen in multiple nodes. The model is designed to optimise the quantity of hydrogen injected to maintain pressure, gas flows, and gas quality indexes (Wobbe index (WI) and higher heating value (HHV)) within admissible limits. This study also presents the maximum injection allowable of hydrogen correlated with the gas quality index variation. The model has been applied to a case study of a gas network with four distinct scenarios and implemented using Python. The findings of the case study quantify the maximum permitted volume of hydrogen in the network, the total savings in natural gas, and the reduction in carbon dioxide emissions. Lastly, a sensitivity analysis of injected hydrogen as a function of the Wobbe index (WI) and Higher Heating Value (HHV) limits relaxation.

Abstract
Reducing the gap between renewable energy needs and supply is crucial to achieve sustainable growth. Hydroelectric power production predictions in several Madeira Island catchment regions are shown in this article using Long Short-Term Memory, LSTM, networks. In order to foresee hydro reservoirs inflows, our models take into account the island's dynamic precipitation and flow rates and simplify the process of water moving from the cloud to the turbine. The model developed for the Socorridos Faja Rodrigues system demonstrates the proficiency of LSTMs in capturing the unexpected flow behavior through its low RMSE. When it comes to energy planning, the model built for the CTIII Paul Velho system gives useful information despite its lower accuracy when it comes to anticipating problems.