Summary The implementation of mobility restrictions and home office schemes due to the COVID‐19 pandemic have influenced electricity consumption patterns and levels. This study analyzes the effect of physical distancing measures regarding mobility on the energy consumption trends for the Brazilian energy system and its subsystems (Northeast, North, South, and Southeast‐Midwest). Trends were evaluated by the Joinpoint software, and the analysis comprehended the period between January 1 and May 27, 2020. Daily load data was grouped into weeks, with the calculation of weekly percentage changes considering a 95% confidence interval and p < 0.05. The weekly electricity loads were compared in the periods before and after the isolation decrees were enforced in Brazil (March 15, 2020). Statistically significant decreases were observed in the levels of electricity consumption, with trends represented by two joinpoints. Due to the different profiles of consumption across the geographic regions, the resulting electricity dynamics were also different. This is the first study to employ joinpoint analysis for the calculation of energy consumption trends focusing on the COVID‐29 pandemic. Data presented herein is unique, in its focus on Brazil, which enables more accurate implications to be drawn for Brazilian policy makers.

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Besides satisfying the energy demands of buildings, distributed generation can contribute toward environmental conservation. However, determining the best configuration and operational strategy for these systems is a complex task due to the available technology options and the dynamic operating conditions of buildings and their surroundings. This work addressed the synthesis and optimization of an energy system for a commercial building (hotel). Electricity, hot water, and cooling demands were established for a hotel located in Northeast Brazil. The optimization problem was based on mixed-integer linear programming and included conventional equipment, solar energy resource (photovoltaic and thermal technologies), and biomass. The objective function of the optimization was to minimize annual economic costs, which involved considering the capital and operation costs. A reference system was established for comparison purposes, where energy demands were met conventionally (without cogeneration or renewable energy), whose annual cost was BRL 80,799. Although the optimal solution did not rely on cogeneration, it benefited from the high degree of energy integration and had a total annual cost of BRL 24,358 (70% lower). The optimal solution suggested the installation of 70 photovoltaic panels and used biomass (sugarcane bagasse) to operate a hot water boiler. Solar collectors for hot water production were not part of the optimal solution. Sensitivity analyses were also carried out, varying the electricity and natural gas tariffs, and the type of biomass employed, but the configuration of the system did not change compared with the optimal economic solution.

CDD 658.5 Elaborado por Maurício Amormino Júnior-CRB6/2422 O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores. 2019 Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais.