3. OCCUPANT BEHAVIOUR MODELLING OPPORTUNITIES IN THE CURRENT DESIGN
3.2 Case Study 2 – Residential Single Family Building [150]
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occupants’ behaviour. More advanced, stochastic thermostat setpoint adjustment algorithms are available in literature ([82] [64] [148] [149]). However, application of these models was not realistic in this project as the required effort was well beyond the project budget.
A sample-office retrofit was proposed to the owner to test the occupant-education program effectiveness and other intervention measures on a small scale to have exact energy-saving figures in the building. This reference office is still under consideration. In case the owner decides to build it, installation of an extensive monitoring system is planned.
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by sustainable consultancy by a team of two where I followed each step of the methodology, investigated owner’s needs, conducted simulations and provided optimal solutions for the owner.
Daylight simulations have been carried out by my colleague. Below, the occupancy-related sensitivity analysis process is described.
FIGURE 11 - FLOWCHART OF THE METHODOLOGY DEVELOPED
The step of occupancy-related sensitivity analysis is highlighted with a black frame on Figure 11 above. With sensitivity analyses I could gain information on the extent of influence that an external factor may have on the energy consumption of our building designed. The most important external factors that have the most influence on the energy use are the weather conditions and the occupant behaviour patterns. [151] [152].
It was investigated what the order of magnitude of change is in annual energy consumption patterns after a possible change in occupant behaviour. As part of this set of sensitivity analysis, the effect of total occupant number change and heating/cooling setpoint adjustments are considered. Afterwards, the design decisions made during the process should be revised taking into account results of sensitivity analyses to ensure that the building designed will be able to meet future requirements of energy-efficient operation considering that the annual energy consumption is robust enough in case of different occupancy scenarios as well.
3.2.3 Input Parameters of Occupancy-Related Sensitivity Analysis
The sensitivity the proposed building’s yearly energy consumption (heating and cooling end energy usage) was investigated in case the number of inhabitants and building usage change. During the design process the future, long-term plans of the SFH owner was investigated. The baseline case was when 4 residents occupy the building. In this case, three bedrooms and living areas setpoints were set to 26°C for summer, 20°C for winter according to local thermal comfort standards. Occupants carried out actions (window opening, shading control overwrite, manual lighting control and thermostat setpoint modifications in their living spaces and bedrooms.
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The sensitivity analysis was carried out for scenarios that represented the assumed future building occupancy of the SFH:
• 2 residents: 2 adults, both working:
children bedrooms and guestroom setpoints set back: 28°C for summer, 18°C for winter, internal heat gains are decreased proportionately compared to the proposed case (4 residents), shading control overwrite, other actions are not possible in rooms unoccupied.
• 3 residents: 2 adults and one child
one bedroom and guestroom setpoints set back: 28°C for summer, 18°C for winter, internal heat gains are decreased proportionately, shading control overwrite, other actions are not possible in rooms unoccupied.
• 4 residents (used as baseline): 2 adults and 2 children
guestroom setpoints set back: 28°C for summer, 18°C for winter, shading control overwrite, other actions are not possible in guestroom.
• 5 residents: 2 adults and 2 children and one grandmother
every room is fully heated, cooled, shading control overwrite, other actions are possible.
3.2.4 Application of Occupant Behaviour Modelling
The sensitivity of the proposed building’s yearly energy consumption (heating and cooling end energy usage) was investigated in case the number of inhabitants and building usage change. Results of the heating consumption sensitivity analysis are shown on Figure 12. There is a tendency that in case of scenarios with more residents, the heating energy consumption is larger. The annual deviation of heating energy consumption is in scenarios 2, 3 and 5 residents compared to the proposed 4 residents scenario -6%, -4% and +10% respectively.
FIGURE 12 - RESULTS OF THE HEATING CONSUMPTION SENSITIVITY ANALYSIS
Results of the cooling consumption sensitivity analysis are shown on Figure 13. A stronger tendency is displayed on the change in cooling energy consumption in case of the scenarios compared to the
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heating energy use investigation. The annual deviation of cooling energy consumption is in scenarios 2, 3 and 5 residents compared to the proposed 4 residents scenario -20%, -2% and +16% respectively.
FIGURE 13 - RESULTS OF THE COOLING CONSUMPTION SENSITIVITY ANALYSIS
3.2.5 A Guideline for Residential Building Design Process, Conclusion
In case of the sensitivity analysis on occupancy change, it was found that the heating energy consumption is not changing significantly. It is assumed that the difference was small because the change in internal heat gains and the setback in zones unoccupied had adverse effects on heating energy demand and thus these phenomena balanced each other. On the other hand, large deviations could be seen in the annual cooling energy consumption of the building (16-20%). It can be stated that in this case the changes in each scenario affected the yearly cooling energy consumption in the same direction. E.g. in case the internal heat gains are decreased and the shading control cannot be overwritten in most of the rooms, the cooling consumption is lowered by both modifications.
The methodology developed could greatly support the design process. The architectural project team was aware of the input data needed, analyses carried out, the outcomes of the analyses and the necessary design changes to carry out during the whole design process. It resulted in a high-performance, sustainable building design in a very efficient way.
This method applied to investigate the energy performance sensitivity of the building for occupancy scenarios was the method that could be fitted into this practice-oriented design project. In the future, more occupant behaviour types could be modelled and considered in a resource-efficient way to enhance the design process.
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