Abstract
Energy allocation rules are one of the core aspects of collective self-consumption (CSC) regulations. It allows final consumers to share their surplus generation with other CSC members, while keeping their full rights as consumers, i.e., maintaining a supply contract with the retailers of their choice. Some European Union member states regulations use allocation coefficients so that local allocations are integrated with wholesale settlement and directly affect the retailers' billing. Several AC methods have been proposed so far, each one adapted to distribution system operators' settlement procedures with specific rules that can impact the benefits that each CSC member obtain. This paper analyses, assesses and compares two relevant AC methods, namely pre-delivery fixed AC and post-delivery dynamic AC, by developing a settlement formulation for a community with members with flexible assets and different opportunity costs. AC policy recommendations based on findings are provided.

Abstract
This research study presents an optimized approach for charging electric vehicles (EVs) in existing residential multi dwelling buildings. The proposed solution tackles the problem in two distinct, but complementary ways. First it takes advantage, in a novel way, of the existing electrical infrastructure by taping directly into the main feeder of the building, second it distributes the power in real time by leveraging in an optimized methodology. The aim of this methodology is to minimize the discrepancy between the desired and final state of charge (SOC) of EVs by the end of each charging session. To achieve this, the method leverages on commuting and charging preferences of EV owners, as well as the electrical infrastructure of residential buildings. To dynamically adjust the charging power for each EV in real-time, an optimized charging management system is employed. This system solves a non-linear minimization optimization problem that considers various parameters, including the initial SOC of each EV, the desired final SOC, the available charging time, and the available charging power. To assess the effectiveness of the proposed methodology, comparative analysis was conducted against a baseline methodology commonly used in practice. The results show that the optimized approach significantly outperforms the non-optimized methods, particularly in high demand scenarios. In these scenarios, the optimized methodology allows for a 200% increase in the supplied energy to the buildings' EV fleet, as well as more than doubling the range made available to users when compared to traditional approaches. In conclusion, this research work offers a robust and effective solution for charging EVs in residential buildings.

Abstract
This work compares six AC/DC power conversion chain topologies commonly employed by industrial companies for implementing electrolyzers. The main purpose is to help identify the eventual advantages of joining the traditional high-power rectifiers to an additional stage based on DC/DC conversion. The comparison is based on the current ripple, power factor, total harmonic distortion, scalability, and solution complexity. A Simulink model corresponding to each topology was developed to determine comparison criteria. The procedure consists of performing a steady-state analysis of each topology through simulations to obtain the main waveforms and the values of the established criteria and then calculating the scores for each technical solution. The findings indicated that the 24-pulse diode bridge rectifier plus DC-DC without interphase reactor exhibited the best performance. © 2024 IEEE.

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 paper investigates the stability of a converter-dominated islanded power system when the island’s battery energy storage converters are operated in different control modes (Grid Forming and Grid Following) and combined with different volumes of synchronous compensation. The study is conducted in a realistic simulation model of the future Madeira island, where no thermal generation is present, and the share of converter-based Renewable Energy Sources is large (75 to 80 % of instantaneous penetration). The impact of the different combinations of synchronous condensers and BESS converter control modes on the system stability is evaluated using a stability index-based approach that accounts for multiple operation scenarios. In this procedure, the system’s dynamic response to the reference disturbances (short-circuits in the Transmission and Distribution Network) is obtained via RMS dynamic simulation and is then analyzed to extract two stability indices (Nadir and Rocof). Such indices are computed for the synchronous generator speed and the grid electrical frequency (measured in different points using a PLL) and are later used as the basis for discussion and conclusion drawing.

Abstract
The environmental impact on the energy sector has become a significant concern, necessitating the implementation of Home Energy Management Systems (HEMS) to enhance the energy efficiency of buildings, reduce costs and greenhouse gas emissions, and ensure user comfort. This paper presents a novel approach to provide optimal day-ahead energy management plans in smart homes with Photovoltaic/Thermal (PVT) systems, aiming to achieve a balance between energy cost and user comfort. This multi-objective problem employs the Non-dominated Sorting Genetic Algorithm III as the optimization algorithm and the Nonlinear Auto-regressive with External Input to forecast the day-ahead meteorological variables, which serve as inputs to predict the PVT electrical and heat production in the thermal resistance model. The HEMS benefits from the time-of-use tariff due to the flexibility provided by the energy storage from a battery bank and a boiler. Furthermore, it performs a load scheduling for 10 controllable loads based on three feature parameters to characterize occupant behavior. A study case analysis revealed a cost reduction of approximately 66% in the solution close to the knee of the Pareto curve (S3 solution). The environmental impact on the energy sector has become a The PVT heat production was sufficient to meet the thermal demand of the showers. The proposed hybrid battery management model effectively eliminated the export of electricity to the grid, reducing consumption during peak periods and the maximum peak demand.