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The use of renewable energy, notably solar and wind energy, has grown exponentially in Brazil. Consumers can generate their energy using renewable sources, whether interconnected to the distribution system (on-grid) or not (off-grid). In this paper, a fuzzy method is developed for the recommendation of solar and wind sources, for any location in the Brazilian territory. In many aspects, it can be viewed as a representation of human decision-making using sets and inference rules and also can be with vagueness and uncertainty, being very useful to idealize recommendation systems. Georeferenced and historical data were obtained from 2003 to 2019 on solar irradiation and wind speed, and electricity consumption until 2021. With the energy generation data from photovoltaic panels and wind turbines, this method allows us to propose installed areas by each technology and obtain the membership of fuzzy recommendation between solar, wind, both solar and wind, unfeasible or hybrid. In addition, a long short-term memory neural network and the seasonal autoregressive integrated moving average model were used to predict consumption for more than 30 months ahead, allowing the recalculation of fuzzy memberships and updating the installation area by respective technologies. As a result, the recommendation is given as the installed area (m2) of each technology per km2 of consumer units, as a function of the regional consumption density (MWh/km2). It can be concluded that it is possible to plan the viability of the type of renewable energy used, according to regional characteristics for smaller consumer units (farms, cooperatives, industries, consortiums), given the diversity of these factors in the huge Brazilian territory. This methodology is in line with the Brazilian Normative Resolution that authorizes the generation of energy by landowners. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the possibility of using daylight as the main source of light for learning and teaching activities in a classroom building of the Universidade Tecnológica Federal do Paraná, in Curitiba, Brazil. Beginning with a survey on light bulb and luminaire types used in the building and on the potential of daylighting in such environments, six different classroom types with different solar orientations were selected for analysis. The research methods included the estimation of daylighting potential from obtained daylight coefficients (DCs) for periods of the year and sky conditions, other than those of the onsite measurements; the evaluation of conformity of the lighting system to the Brazilian RTQ Code (Regulamento Técnico de Qualidade), an energy consumption rating system, aimed at reducing electric energy consumption in office buildings; the estimation of electric energy demand for a combined use of daylighting and lighting system; the proposal of an efficient lighting system; and cost assessment using payback analysis. Results suggest energy savings of up to 94% when integrating daylight with the artificial lighting system, a payback within the range of 22-60 months for a complete substitution of the existing lighting system for a more efficient one. [ABSTRACT FROM AUTHOR]

This paper compares the use of sugar cane and corn for the production of ethanol, with a focus on global warming and the current international debate about land use competition for food and biofuel production. The indicators used to compare the products are CO2 emissions, energy consumption, sugar cane coproducts, and deforestation. The life cycle emission inventory as a methodological tool is taken into account. The sustainability of socioeconomic development and the developing countries’ need to overcome barriers form the background against which the Brazilian government energy plans are analyzed. [ABSTRACT FROM AUTHOR]