Abstract
Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms' cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

Abstract
In Portugal, labour availability has been revealed as a key factor for the activity, particularly in mountain viticulture. The latest statistics present worrying values that could undermine the production of quality wine and the attractive set of wine landscapes considered as a potential resource for tourism development. The Douro Region is one of the main Portuguese wine regions, characterized by a prominent and accentuated mountain viticulture. This paper aims to simulate the behaviour of its farms about the changes in the price of labour, through Agent-Based Models (ABM). The MATLAB software was used to obtain periodic functions adjusted to the data that characterize the relevant variables, obtained from face-to-face surveys of 110 farms, and taking into account the data provided by PTFADN. Subsequently, the ABM software (NETLOGO) was selected to simulate the next 100 years, familiarizing the real dynamics based on the previously considered data. Depending on the price of labour at the end of the simulation horizon, with a grape price of 0,77 €/kg, from the 300 initially existing farms survive between 127 and 231 (42,3 - 77%). In a more optimistic scenario, with a grape price of 1,17 €/kg, the survival rate ranges between 72.1 and 93.2%. © 2021

Abstract
In the coming years, many countries are going to bet on the exploitation of offshore wind energy. This is the case of southern European countries, where there is great wind potential for offshore exploitation. Although the conditions for energy production are more advantageous, all the costs involved are substantially higher when compared to onshore. It is, therefore, crucial to maximize system efficiency. In this paper, an optimization model based on a Mixed-Integer Linear Programming model is proposed to find the best wind turbines location in offshore wind farms taking into account the wake effect. A case study, concerning the design of an offshore wind farm, were carried out and several performance indicators were calculated and compared. The results show that the placement of the wind turbines diagonally presents better results for all performance indicators and corresponds to a lower percentage of energy production losses.

Abstract
Teaching project management and industrial optimization to engineering students requires real-world experiences in which they can explicitly integrate, apply and develop work-ready skills, such as critical thinking, communication, and teamwork. This paper presents an exploratory case study research describing an online Project-based Learning (PjBL) experience aimed at tackling the challenge of decreasing the ecological footprint in the university campus generated by the local locomotion of students from university-home and/or home-university. The experience was implemented from February to June 2020, in the middle of the COVID-19 pandemic, with 9 participating students enrolled in the 'Industrial Management I' course, part of the Master of Science in Mechanical Engineering at the University of Tras-os-Montes and Alto Douro (UTAD), Portugal. We firstly describe the course in terms of the key driving question, the learning goals, the educational activities, the collaboration among students, the scaffolding technologies, and the tangible artefacts produced. We further discuss the preliminary results of the study by taking into account the main tangible learning artefact produced by the students - a carpooling model proposal for the UTAD student community - as well as the data collected from a post, self-completion questionnaire on students' perceptions about the PjBL experience. Finally, we outline implications for the teaching practice and some concerns that need to be addressed in future course editions.

Abstract
The increase in the world's population combined with the development of new economies has led to a large scale increase in the demand for energy resources. New technologies have emerged that allow for the maintenance of the energy supply. Renewable sources and energy storage systems (ESS) are emerging as a crucial option for the development of Smart Grids. Using a Mixed Integer Linear Programming (MILP) optimization model, the effects of renewable production sources and storage systems on an electrical grid were studied, in order to maximize the profit of a Virtual Power Plant (VPP). The obtained results allowed us to verify the efficiency of the proposed method. The placement of renewable producers and the ESS, as well as the management optimization of the purchase and transfer process of the stored energy definitely increased the profit of VPP. The use of these technologies also improves the voltage profile and decreased the active power losses by 84% along with the network.

Abstract
Nowadays, power distribution systems face some challenges related to power losses minimization and voltage stability improvement along the networks. These challenges can also be a big opportunity to develop smarter and more efficient distribution networks, ensuring the continuity of service and the power quality supplied to consumers. At the same time, there are several international standards that regulate the power quality levels required for distribution networks.This paper addresses deeply these issues and provide a solution to solve both of these problems using Distributed Generators (DG) on optimal locations of the grid. The proposed method will analyze the injection of both real and reactive power in a regulated IEEE-69 bus system. In the first stage, the voltage and loss sensitivity of the load flow analysis is calculated using a MatLab algorithm. In a second stage, the methodology uses the voltage stability index (VSI) to obtain the optimal location of the DGs to ensure the best results of both, power loss and voltage stability for the grid. The obtained results show the good effectiveness of the proposed method.