Wednesday, 29 June 2016: 11:00 AM-12:30 PM
Research Summit
Chair:
Didier Thevenard, Ph.D., P.E., Numerical Logics Inc.
Technical Committee: 04.02 Climatic Information
The common practice in building performance modeling is to use ‘Typical Year’ weather data. Such data is statistically selected from the long-term record based on representative statistics for solar radiation and dry bulb temperature. However, although the use of a single typical year is convenient, it often leads to severe inaccuracies in the estimation of building loads and energy consumption. It is time to rethink alternatives to the use of Typical Year files. This seminar provides a deeper understanding of the problems linked to the use of Typical Years and walks the audience through several alternatives.
1 How Much Does Energy Use Vary with 'Actual' Weather from Year to Year?
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Drury Crawley, Ph.D., Bentley Systems, Inc. |
Historically, building simulation users have used ‘typical’ year weather data to represent climatic conditions for a location or region. With advent of increasingly powerful computers, using a single year of data is no longer necessary. Prior studies have shown that a single year of data often does not well represent the range of climate conditions over a period. We demonstrate how several sets of international typical meteorological data sets compare to the actual period of record that they represent, and demonstrate the inter-annual variability of energy use due to real weather data in comparison to TMY-type data.
2 How Much Do HVAC Loads Change Due to the Variability of Year-to-Year Weather?
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Yu Joe Huang, White Box Technologies |
Typical year weather files give a convenient snapshot of the likely weather conditions in a location. However, they provide no information of the year-to-year variability of the weather, which can have a dramatic impact on a building's heating and cooling energy use. This presentation shows a procedure using the variable-base degree day method to determine from the period of record which years would produce the highest heating or cooling loads and calculate the standard deviation in loads from the typical year. These results are building-specific, depending on how sensitive is the building to conduction, convection, or radiation heat flows.
3 Understanding the Temporal and Spatial Variability of New Generation Gridded Tmys
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Anthony Lopez |
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Aron Habte, NREL |
Typical Meteorological Year (TMY) data sets provide industry standard resource information for building designers and the solar industry. Historically, TMY data sets were only available for certain locations, but current TMY data sets are available on the same grid as the new 4-km by 4-km gridded National Solar Radiation Database (NSRDB) data and are referred to as the gridded TMY. In this presentation, we analyze the temporal and spatial variability of the typical year data sets, thereby providing insight into the representativeness of a particular TMY data set for use in building performance modeling.