Energy diagnosis methodologies have been incorporating energy consumption and energy
generation systems into their analysis, making it possible to classify energy-self-sufficient
buildings as Near Zero Energy Buildings (NZEB) or Positive Energy Buildings (PEB). In
electric mobility, the increased use of electric vehicles (EVs) brings challenges and
opportunities in electricity consumption, management and efficiency. The impact of this robust
and growing load when integrated into new and existing buildings is not yet considered in
performance assessments. Consequently, the methodologies for obtaining certifications and
labels do not consider the load of this system as an individual end-use. For buildings with energy
efficiency (EE) and self-sufficiency labels, introducing EVs can result in the rating being
downgraded due to increased energy consumption. Therefore, analyzing the impact of
integrating EVs into buildings aims to support the formulation or revision of energy diagnosis
methodologies that include EV charging systems integrated into buildings. This thesis evaluates
the influence of EV charging in buildings with the NZEB/PEB label from the Brazilian Building
Labeling Program (PBE Edifica). Using on-site surveys, computer modelling and thermo energetic analysis with software such as OpenStudio and EnergyPlus, an energy rating was
carried out on a building in Belém, State of Pará, Brazil. Subsequently, energy flow simulations
using probabilistic models with the Monte Carlo method were run in OpenDSS software to
examine the impact of integrating EVs without (scenario 01) and with (scenario 02) the
implementation of demand-side management techniques. Analysis using the labelling
methodology showed that the building has an EE level C rating and NZEB self-sufficiency.
Scenario 01 generated a 69.28% increase in energy consumption, reducing the EE level to D
and resulting in the loss of the NZEB class. Scenario 02 increased consumption by 40.50%, a
lower percentage than scenario 01 and guaranteed the return of the NZEB class lost in scenario
1, but did not return the EE level to class C. The results highlight the need for immediate and
comprehensive energy management strategies. However, these strategies are not sufficient if
other consumption restrictions or EE measures are not applied to other systems in the building.
To this end, EE measures were proposed and evaluated in the air conditioning and lighting
systems. Subsequently, an equation was drawn up to indicate the maximum level of energy
X
consumption that could be increased without compromising the building's energy performance
and NZEB rating. Finally, OpenDSS software was used to simulate the increased availability of
EV charging after the retrofit. With the proposed retrofit, the building improved its EE ratings
by three levels, and the NZEB rating percentage increased by 33.28%. These measures also
increased the EV charging load by 20% while maintaining the maximum EE level and NZEB
rating.
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