Electric power systems have experienced the rapid insertion of distributed renewable generating sources and, as a result, are facing planning and operational challenges as new grid connections are made. The complexity of this management and the degree of uncertainty increase significantly and need to be better estimated. Considering the high volatility of photovoltaic generation and its impacts on agents in the electricity sector, this work proposes a multivariate strategy based on design of experiments (DOE), principal component analysis (PCA), artificial neural networks (ANN) that combines the resulting outputs using Mixture DOE (MDOE) for photovoltaic generation prediction a day ahead. The approach separates the data into seasons of the year and considers multiple climatic variables for each period. Here, the dimensionality reduction of climate variables is performed through PCA. Through DOE, the possibilities of combining prediction parameters, such as those of ANN, were reduced, without compromising the statistical reliability of the results. Thus, 17 generation plants distributed in the Brazilian territory were tested. The one-day-ahead PV generation forecast has been considered for each generation plant in each season of the year, reaching mean percentage errors of 10.45% for summer, 9.29% for autumn, 9.11% for winter and 6.75% for spring. The versatility of the proposed approach allows the choice of parameters in a systematic way and reduces the computational cost, since there is a reduction in dimensionality and in the number of experimental simulations.

Grades and other student academic indicators are the most evaluated parameters in studies about teaching and learning. However, several authors point out that these indexes, alone, are not enough to explain the students' performance. To understand the predictors that facilitate or compromise learning in higher education, it is neces-sary to consider other variables related to students, teachers, and the teaching con-text. Thus, this paper presents a multivariate model for assessing student performance in online courses. The model was tested in the context of the COVID-19 pandemic with undergraduate students in Engineering. The course was Calculus 2. Data were analyzed using multivariate statistical analysis techniques. Among the 10 variables tested in the model. Three variables were significant and showed that the students' performance in Calculus 2 was impacted by: family income, cognitive and self-regulatory learning strategies, and teachers' instructional events. The main con-tribution of the study is the construction of a multivariate model that can be replicate in other contexts. In practices, professors and managers will have inputs to better plan the disciplines and avoid increasing retention and dropout rates.

Companies claim that gaps in the development of transversal skills in young people aged 18 to 24 compromise employability rates. Research warns that, both inside and outside organizations, all educational actions must be adequately planned to avoid offering ineffective training. Given this scenario, the objective of this article is to describe the process of constructing an instructional plan to serve as a reference for professionals working in people development. For this article, the training topic was transversal skills for youth employability. The collected data were analyzed with the support of the heuristic logic matrix. The planning was based on theoretical tools and instructional technologies in the field of training, development, and education (TD&E). The main contribution of this study is the provision of instructional designs for use in training of any nature, in a face-to-face format. Keywords: youth employability, instructional planning, training program. Las empresas argumentan que las brechas en la formación de competencias transversales en jóvenes de entre 18 y 24 años comprometen las tasas de empleabilidad. Investigaciones alertan que, dentro y fuera de las organizaciones, todas las acciones educativas deben ser planificadas adecuadamente, a fin de evitar la oferta de capacitaciones sin efectividad. Dado este escenario, el objetivo de este artículo es describir el proceso de construcción de capacitaciones efectivas para los profesionales que trabajan en la capacitación de personal a fin de ser una referencia para los profesionales que actúan en esta área. Para este artículo, el tema de la capacitación fue competencias transversales para la empleabilidad de jóvenes. Los datos recopilados fueron analizados con el apoyo de la herramienta Matriz Lógica Heurística. La planeación se apoyó en tecnologías instruccionales del área de Capacitación, Desarrollo y Educación (CDE). La principal contribución de este estudio es la disponibilidad de diseños instruccionales para su uso en capacitaciones de cualquier naturaleza, en formato presencial. Palavras-chave: empleabilidad juvenil, planificación de la instrucción, programa de formación. Empresas alegam que lacunas na formação de competências transversais em jovens com idade entre 18 e 24 anos comprometem as taxas de empregabilidade. Pesquisas alertam que, dentro e fora das organizações, todas as ações educacionais devem ser planejadas adequadamente, a fim de evitar a oferta de treinamentos sem efetividade. Dado esse cenário, o objetivo desse artigo é descrever o processo de construção de um planejamento instrucional para ser uma referência aos profissionais que atuam com desenvolvimento de pessoas. Para esse artigo, a temática do treinamento foi competências transversais para empregabilidade de jovens. Os dados coletados foram analisados com o apoio da ferramenta Matriz Lógica Heurística. O planejamento teve como base teórica ferramentas e tecnologias instrucionais da área de Treinamento, Desenvolvimento e Educação (TD&E). A principal contribuição desse estudo é a disponibilização dos desenhos instrucionais para uso em treinamentos de quaisquer natureza, em formato presencial. Palavras-chave: empregabilidade juvenil, planejamento instrucional, treinamento de pessoal.