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Climate Surfaces
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A Quantitative, Building Relevant Description of Climates: The Climate Surfaces
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Collaborator: Harald Burmeister, PhD
Project finished in 1996.
Contacts: B. Keller
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The today's available climate data as design temperature, heating-degree days etc. do not take into account the dynamic behaviour of buildings and especially not the time-correlation between solar radiation and outside air temperature.
The simulation programs on the other hand are too complicated to be used in an early state of planning and moreover reveal only specific results for specific situations with no strategic applicability.
The analysis of the equation of state of a room however allows the reduction of the complicated set of parameters to only three most important parameters:
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- generalised loss factor K
- time-constant (thermal memory)
- solar gain-to-loss-ratio
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By separating out the loss-factor as a linear one, we where able to create generalised heating-degree-days taking into account solar gains and being represented by so-called climate-surfaces. For each considered climate and each considered control strategy we get one climate surface.
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Example for the heating energy:
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With the aid of such climate-surfaces
- different climates can be quantitatively compared
- the energetic position of a room can be determined
- strategies of best improvement can be found.
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The aspects of cooling energy, heating power and cooling power can be treated similarly.
With the method of the climate-surfaces different control strategies as night set back, internal heat sources, night cooling, etc. can be analysed in a very fundamental way, in respect to the room characteristics (room parameters tau, gamma) and the considered climate: From the position on the climate surfaces it can easily be shown
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- for what parameter range (,) the considered control strategy does not lead to a significant improvement for the energy consumption
- for what parameter range (,)the considered control strategy has an influence on the energy consumption
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This Method has been tested against well monitored and documented real test buildings with very good agreement, even better than the results of more complicated simulation programs such as Suncode, DOE etc.
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With this method, a design tool has been found that shows in a strategic way the connections between the climates and the buildings. Though it won't show a precision of a few percent it permits to check in a very early planning state principal decisions on their consequences for the energy consumption. Considering that in many much more complex simulation programs quantities as air infiltration and the users behaviour are treated in a very rudimentary way, the precision of the presented method can be estimated as good, even for definitive design purposes.
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