In a previous article we outlined the concept of eXtreme Meteorological Year (XMY) as a hypothetical data set representing an extreme year of weather. An XMY for HVAC represents conditions that produce extremely high or low energy consumption across the entire year (note the focus on energy, as distinct from the extreme design conditions used for HVAC sizing which evaluate peak power demand).
As discussed previously, XMY data is important in building energy simulations to give us an insight into building energy performance as climatic conditions vary in the near future. If Representative Meteorological Year (RMY) data can tell us about the expected energy demand, the XMY data indicates the uncertainty due to climate variability.
In our work to develop XMYs for HVAC, one of the first questions to arise was whether an “extreme” year of climate should be considered as extreme for all building types.
To answer this, we ran historical weather data from 1990 to 2017 for Canberra and Brisbane through a series of EnergyPlus simulations to calculate heating and cooling energy data for our three archetype buildings: Supermarket, 3-storey and 10-storey office buildings. The analysis of the data were conducted for heating and cooling separately as well as combined, for individual building types and as a collective of buildings, over yearly and monthly time periods. Our results indicate a reasonable correlation between the three building types.

Correlation of HVAC energy use between the three building archetypes in Canberra

Pairwise comparison of the annual cooling energy use between the 3-storey and 10-storey office buildings in Canberra
We have also found that the energy results fit a rough Gaussian distribution (bell curve). This is important as it means that standard statistical techniques can be applied to the next stages of analysis which we will discuss further in a future post.
Readers interested to engage with us in our development of XMY data are invited to make contact soon via exemplary.energy@exemplary.com.au

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