Abstract
The optimal power flow (OPF) is one of the most noticeable and integral tools in the power system operation and control and aims to obtain the most economical combination of power plants to exactly serve the total demand of the system without any load shedding or islanding through adjusting control variables to meet operational, economic, and environmental constraints. To achieve this goal, the successful implementation of an expeditious and reliable optimization algorithm is crucial. To solve this issue, this research proposes an enhanced democratic political algorithm (DPA), which can effectively solve multi-objective optimum power flow problems. The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. For the sake of practicality, the objectives with innate differences such as total emission, active power loss, and fuel cost are selected. Due to the practical limitations in real power systems, additional restrictions including valve-point effect, multi-fuel characteristics, and forbidden operational zones, are also considered. The proposed approach is tested and validated on IEEE 57 bus and IEEE 118-bus systems with different case studies. Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. The study results illustrate the effectiveness of the proposed method in handling different scales, non-convex, and multi-objective optimization problems.

Abstract
This work was developed to improve the costing process of new products within the Product Development Department of a furniture manufacturer. It consisted of creating a parametric cost estimation model based on applying simple and multiple linear regressions, considering the existing data of the products produced and their respective costs. The proposed model considers the cost estimation of creating a product that covers the materials and operations costs. The suitability of the different independent variables was studied by applying simple and multiple linear regressions. A set of functions that return an estimate of the cost as a function of these predictor variables was obtained. The model built with the functions obtained provides the materials and operations cost estimation. The results indicated that 75% of the tests performed show an estimation error of less than 2% in the total cost of a product. Incorporating this model in a tool with the purpose of cost estimation brings the ability to predict prices faster, improving the internal process of obtaining costing and enhancing the analytical capacity of the team in the relentless pursuit of cost minimization and value creation.

Abstract
The sense of presence is an important aspect of virtual reality experiences, being increasingly researched in educational contexts for its potential association with learning outcomes. A panorama of how these investigations have been conducted could help researchers and practitioners to harness this potential and find new directions. A systematic literature review was conducted to contribute to this perspective, with a comprehensive analysis of 140 primary studies recovered from five worldwide databases. The results show an overview of 24 years of research, with a summarization of areas, factors, and methodological approaches that have been the focus of investigation when these three variables of interest (VR, sense of presence, and learning) are together. We conclude with a list of research gaps that need to be addressed and a research agenda, identifying current and emerging challenges.

Abstract

Abstract
The progressive replacement of thermal power plants by converter-interfaced generation, such as wind and solar power plants, reduces the synchronous component available in the system. Additionally, as converter-interfaced renewable energy sources do not directly provide inertia to the power grid, electric power systems are facing a notorious inertia reduction. When facing disturbances affecting the balance between the generation and demand, reduced inertia systems exhibit higher and faster frequency deviations and dynamics. This can result in the disconnection of generation units as well as load shedding, provoking cascading effects that can compel severe power outages. This work examines the impacts of the progressive integration of converter-interfaced renewable energy sources in the frequency stability, considering critical disturbances involving short-circuits in different locations. To simulate the dynamic behaviour of a network containing high shares of renewable energy generation, the IEEE 39-bus system is used while resorting to the PSS/E simulation package. After obtaining a scenario with reduced synchronous generation, the network's stability is assessed in face of key frequency indicators (frequency nadir and Rate of Change of Frequency, RoCoF). Regarding the critical disturbances applied in a low inertia scenario, different control solutions for the mitigation of frequency stability problems are tested and their performance is assessed comparatively. This involves the investigation of the performance of the active power-frequency control in the renewable energy sources, of synchronous condensers, or fast active power-frequency regulation services from stationary energy storage. Moreover, the influence of the location and apparent power of synchronous condensers (SCs) and Battery Energy Storage Systems (BESS) on the frequency indicators is evaluated.

Abstract
This research examines the impact of the COVID-19 pandemic and the Ukraine-Russia conflict on Portugal and Spain's national energy and climate plans. Both countries have updated their plans in response to these events, emphasizing energy efficiency, renewable energy investment, and circular economy principles. Portugal focused on addressing energy poverty and digitalization, while Spain accelerated its energy transition to align with the European Green Deal. Additionally, the Ukraine-Russia conflict prompted measures to enhance energy security and NECPs in both countries. Through a semi-systematic literature review spanning 2020-2023, our study analyzes how these global events shaped national energy and climate plans. The case studies of Portugal and Spain highlight the importance of flexibility and resilience in crafting sustainable energy strategies during such a complex crisis.