Abstract
The United Nations has issued a warning over the limited time for climate disaster prevention. In the last two decades, several countries have set targets to reduce fossil fuel usage and greenhouse gas emissions. These goals are tracked through the adoption of energy systems that prioritise efficiency and low-carbon alternatives, in alignment with the Sustainable Development Goals outlined by the United Nations. In the winemaking sector, the wine produced in the European Union comprised 65 % of the worldwide total from 2014 to 2018, with vineyards making up 4.7 % of its farms in 2020. Electricity is the primary source of energy used in vineries, accounting for around 90 % of the total energy consumption. The energy consumption associated with winemaking is mostly attributed to two key processes: fermentation, which accounts for 45 % to 90 % of the entire energy consumption, and bottling and storage, which contribute around 18 % of the overall energy consumption. The aim of this article is to provide an integrated review of energy efficiency in wineries through examining 144 academic publications. The selected publications cover various aspects, including sustainable energy utilisation in the wine industry, thermal performance analysis of buildings, energy efficiency assessment of systems and technologies, and the integration of renewable energy sources. A link has been established between the geographic distribution of academic publications and wine -producing countries. In relation to European publications, it is observed that research funding is associated with the energy directives of the European Union. It can also be concluded that wine customers are pushing for environmentally friendly practices. However, not everyone in the winemaking sector is moving in the same direction or at the same pace. To identify areas for improvement, winemakers must have supporting tools to manage energy use. Systems optimisation, monitoring, and accounting can be used to decrease energy consumption in winemaking processes or equipment. Progresses on sustainable energy use through greater energy efficiency and share of renewable energies in the wineries can contribute to the reduction of greenhouse gas emissions, and consequently, brings the wine industry closer to climate neutrality.

Abstract
Several sectors, such as agriculture and renewable energy systems, rely heavily on weather variables that are characterized by intermittent patterns. Many studies use regression and deep learning methods for weather forecasting to deal with this variability. This research employs regression models to estimate missing historical data and three different time horizons, incorporating long short-term memory (LSTM) to forecast short- to medium-term weather conditions at Quinta de Santa B & aacute;rbara in the Douro region. Additionally, a genetic algorithm (GA) is used to optimize the LSTM hyperparameters. The results obtained show that the proposed optimized LSTM effectively reduced the evaluation metrics across different time horizons. The obtained results underscore the importance of accurate weather forecasting in making important decisions in various sectors.

Abstract
Socioeconomic growth and population increase are driving a constant global demand for energy. Renewable energy is emerging as a leading solution to minimise the use of fossil fuels. However, renewable resources are characterised by significant intermittency and unpredictability, which impact their energy production and integration into the power grid. Forecasting models are increasingly being developed to address these challenges and have become crucial as renewable energy sources are integrated in energy systems. In this paper, a comparative analysis of forecasting methods for renewable energy production is developed, focusing on photovoltaic and wind power. A review of state-of-the-art techniques is conducted to synthesise and categorise different forecasting models, taking into account climatic variables, optimisation algorithms, pre-processing techniques, and various forecasting horizons. By integrating diverse techniques such as optimisation algorithms and pre-processing methods and carefully selecting the forecast horizon, it is possible to highlight the accuracy and stability of forecasts. Overall, the ongoing development and refinement of forecasting methods are crucial to achieve a sustainable and reliable energy future.

Abstract
One of the biggest obstacles when it comes to the electrification of the vehicle fleet is the charging time of an electric vehicle (EV), which means that users of these vehicles, when they need to charge their car, always look for fast charging stations. This is the charging method that has the shortest duration. In the coming years, an increase in the proliferation of electric vehicles will lead to a greater demand for electricity, which in turn will put the distribution network to the test. Since the number of non-linear loads increases day by day, putting the distribution network under increasing stress, it is wise to study the effects of the high penetration of electric vehicles (EV) on the power quality of the network. This paper aims to study the impact of charging EV on the quality of energy in the distribution network. First, an analysis of the harmonics and electronics (non-linear loads) associated with EV chargers will be done. Then, a simulation will be performed on the IEEE 33 network using the Matlab/Simulink simulation software. Finally, a comparison will be made of the results obtained in the simulation and possible ways of mitigating the harmonics that non-linear loads inject into the electricity distribution network. Keywords. Electrical Vehicle (EV), Harmonic Analysis, Matlab/Simulink, EV DC Fast Charger, Non-Linear Loads.

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
In recent years, there has been a significant growth in the use of technologies that rely on natural resources (wind, solar, etc.) as primary sources of energy. The generation originating from renewable sources brings an increased need for adaptation in power electrical systems. Predicting the amount of energy produced by these technologies is a complex task due to the uncertainty associated with natural resources. This uncertainty hinders decision-making, both at the system level and for consumers themselves who are increasingly using this type of technology for self-consumption. This study focuses on classifying solar intensity using imbalanced data, which means that some of the data categories are more prevalent than others. Oversampling techniques are be employed to increase the amount of data, thereby allowing for balanced training data and improving the performance of prediction models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.