Abstract
This research assesses the behaviour of alternative objectives related to maximising the energy self-consumed in renewable energy communities. Three different objective functions are proposed: minimising the grid-supplied energy to the community members, reducing the energy surplus of the community injected into the grid, and maximising the self-consumed energy according to its definition in the Portuguese regulation. Two additional objectives were also considered for comparison purposes, the maximisation of the equivalent CO2 emissions saved and the minimisation of the total community energy cost. The methodology involves formulating and implementing the optimisation problems and discussing the results with a case example, including decreased grid dependency, utilisation of battery storage, and differences in energy trading strategies within the REC. Overall, this research contributes to understanding some alternative objectives that could be considered for the management of the flexible resources of a REC. © The Institution of Engineering & Technology 2024.

Abstract

Abstract
The gold standard methods for real-time core temperature (CT) monitoring are invasive and cost-inefficient. The application of Kalman filters for an indirect estimation of CT has been explored in the literature since 2010. This paper presents a comparative study between different state of the art Extended Kalman Filter (EKF) estimation algorithms and a new approach based on a biomimetic human body response pre-emptive mapping concept. In this new method, a mapping model of the physiological response of the heart rate (HR) change to CT increase is pre-applied to the input of the EKF estimation CT procedure in a near real-time manner. The algorithm was trained and tested using two datasets (total participants = 18). The best performing algorithm with this novel pre-emptive mapping achieved in an average Root Mean Squared Error (RMSE) of 0.34°C while the best state of the art EKF model (without pre-emptive mapping) resulted in a RMSE of 0.41°C, leading to a 17% improvement performance of our novel method. Given these favorable outcomes, it is compelling to assess its efficacy on a larger dataset in the near future.

Abstract
Recently, the uptake of renewable energy has surged in distribution networks, particularly due to the costeffectiveness and modular nature of photovoltaic systems. This has paved the way to a new era of user engagement, embodied by individual and collective self-consumption, and promoted by the EU Directive 2018/ 2001, which advocates for the establishment of Renewable Energy Communities. However, the transposition of this directive varies across Member States, resulting in specific rules for each country. In this work, the impact that different energy sharing models have on the same community is quantitatively assessed. The policy analysis focuses on the regulation of two countries, Italy and Portugal, chosen for the specular ways in which their models operate, respectively virtually and physically. The analysis is supported by a suite of tools which includes two optimization problems for community's operations, one for each analysed regulation, and a set of consumer protection mechanisms, to ensure no member is losing money while in community. Results demonstrate that the sharing model impacts community's optimal operations, optimal battery size and configuration, and members' benefit. As these models are sensitive to different variables, personalized interventions at national level are required.

Abstract
According to the Portuguese Roadmap for Carbon Neutrality 2050 (RNC2050), Portugal aims to achieve carbon neutrality by 2050. To achieve this goal, it is necessary to decrease the consumption of primary energy from non-renewable sources and increase the consumption of energy from renewable sources. Portugal has a high potential for energy production through solar energy, and the country has a large solar potential that can be used. Thus, this work focuses on the study of the reliability of charging electric vehicles through photovoltaic energy, being sized electric vehicles charging stations, with different topologies, for domestic consumption, for different types of user profiles. At the same time this study evaluated technically and economically the proposed solutions. The research concluded that this type of technology proves to be a viable solution, especially if storage systems do not need to be implemented, as the limited useful lifetime of batteries substantially increases investment amortization times. Key words. Photovoltaic Systems, Electric Vehicle, Charging Stations, Energy Efficiency, Techno-Economic Study.

Abstract
The trends of the 21st century are challenging the traditional production process due to the reduction in the life cycle of products and the demand for more complex products in greater quantities. Industry 4.0 (I4.0) was introduced in 2011 and it is recognized as the fourth industrial revolution, with the aim of improving manufacturing processes and increasing the competitiveness of industry. I4.0 uses technological concepts such as Cyber-Physical Systems, Internet of Things and Cloud Computing to create services, reduce costs and increase productivity. In addition, concepts such as Smart Factories are emerging, which use context awareness to assist people and optimize tasks based on data from the physical and virtual world. This article explores and applies the capabilities of context-aware applications in industry, with a focus on production lines. In specific, this paper proposes a context-aware application based on a microservices approach, intended for integration into a context-aware information system, with specific application in the area of manufacturing. The manuscript presents a detailed architecture for structuring the application, explaining components, functions and contributions. The discussion covers development technologies, integration and communication between the application and other services, as well as experimental findings, which demonstrate the applicability and advantages of the proposed solution.