Abstract
In recent years, as a result of population growth and the strong demand for energy resources, there has been an increase in greenhouse gas emissions. Thus, it is necessary to find solutions to reduce these emissions. This will make the use of electric vehicles (EV) more attractive and reduce the high dependency on internal combustion vehicles. However, the integration of electric vehicles will pose some challenges. For example, it will be necessary to increase the number of fast electric vehicle charging stations (FEVCS) to make electric mobility more attractive. Due to the high power levels involved in these systems, there are voltage drops that affect the voltage profile of some nodes of the distribution networks. This paper presents a methodology based on a genetic algorithm (GA) that is used to find the optimal location of charging stations that cause the minimum impact on the grid voltage profile. Two case studies are considered to evaluate the behavior of the distribution grid with different numbers of EV charging stations connected. From the results obtained, it can be concluded that the GA provides an efficient way to find the best charging station locations, ensuring that the grid voltage profile is within the regulatory limits and that the value of losses is minimized.

Abstract
Renewable energy generation technologies, heat pumps or electric vehicle (EV) charging stations use active power electronics such as IGBT or MOSFET for AC to DC conversion with the consequence of emissions in the higher frequency range above 2 kHz (non-intentional supraharmonic emissions) and with an impact to the higher frequency grid impedance. In this study the impact of active power electronics on the higher frequency grid impedance in the range up to 150 kHz is analyzed. As existing grid modelling solutions do not consider these technologies sufficiently, this study analyzes the impact of a vehicle to grid (V2G) chargers to a representative distribution grid considering different grid topologies and different types of V2G chargers. The study shows that the additional capacitance and inductance (LCL filter, DC link capacitor) introduced in the electrical grid causes parallel and series resonances in a wide frequency range starting from 500 Hz up to 50 kHz. The grid topology and the number of V2G chargers connected determines the frequency range and characteristics of resonances. Finally, the major contribution of this study is outlining the importance of considering the higher frequency grid impedance for characterization of supraharmonic emissions (primary vs. secondary emissions) and their propagation.

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.