Robust design and modelling of solar houses: methodology and technologies

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Direct solar gain (AKA passive solar) strategies in houses (detached and row houses) are among the most cost-effective and simplest approaches to significantly reducing total household energy use. They use a combination of large high-performance south-facing windows, thermally-massive materials, and high levels of insulation and air-tightness. However, when designing solar houses using building performance simulation (BPS) many assumptions must be made about occupancy and occupant behaviour (e.g., window openings, electrical appliance use, and heating and cooling setpoints) - despite an [often] high degree of uncertainty. Thus, designers aiming for optimal designs are actually optimizing around a set of assumptions rather than real operating conditions. A greater risk is that the house's performance will be highly-sensitive to the accuracy of the assumptions and that it will under-perform relative to predicted results if and when reality deviates from the assumptions. Rather than attempt to control the the way occupants behave (which has been proven to be very difficult), the proposed research will develop methods for robust solar house design. This entails implementing design features and control strategies that are significantly less sensitive to a range of occupant-related energy use. Monte Carlo analysis methods combined with building performance simulation and a database of probability distributions for all sources of uncertainty will be used to test the robustness of solar designs.Utilizing the robustness framework, the proposed research will develop a multi-zone forced-air system that enables better solar heat gains distributions within a house will be designed. The system will be modelled using BPS and airflow networks to assess energy and thermal comfort performance. A major aspect of this research is focused on assessing the convective heat transfer between charged thermal mass (e.g., a concrete floor warmed by the sun) and the adjacent air. Experimental techniques using a highly-instrumented house will complement modelling approaches.