However, the number of “unmet cooling hours” predicted by the 2040s TMY simulation is a serious concern. When a model shows an unmet cooling hour, it indicates the mechanical cooling system is unable to meet a cooling demand and ultimately that occupants will experience discomfort. The model predicts 712 unmet cooling hours in the 2040s’ scenario. This is likely to occur during the middle eight hours of the day, equating to 89 days — or three full months annually — where building occupants will be too hot. Such conditions are unacceptable to occupants who, in the best case, would be unproductive and, in the worst case, at health risk. Remedies to this situation would likely include modifications such as windowmounted air condition units. Such “tack on” systems are unattractive and inefficient, resulting in increased electricity use and greenhouse gas emissions.
FIGURE 3: TOTAL ANNUAL ENERGY USE INTENSITY (EUI) RESULTS.
What to do? Ensure the weather file you use for building design and performance simulations is an accurate representation of the current climate in your project’s geographic region. Run additional simulations of future scenarios to test potential implications to building performance objectives and occupant comfort. Although building designs need to be based on current weather conditions, it is possible to include provisions to adapt the building, allowing it to continue to perform in the future. Examples of adaptable design include: structures that can accommodate the addition of external shading devices in the future; phase-changing glass; and implementing high-performance passive solutions, rather than mechanical systems, to meet occupant comfort requirements. For a full summary of this study’s findings, refer to the White Paper Modelling Weather Futures, available to read at RWDI.com.
TABLE 1: UNMET HOURS.
Mike Williams is Technical Director and Principal at RWDI Consulting Engineers and Scientists. Jennifer Harmer is Project Coordinator, Sustainability at RWDI Consulting Engineers and Scientists. References ARCC. (2014). A review of downscaling methods for climate change projections. Burlington, Vermont: African and Latin American Resilience to Climate Change (ARCC). Environment Canada. (2010). Canadian Weather Energy and Engineering Data Sets and Canadian Weather for Energy Calculations - Updated User’s Manual. Ottawa: Government of Canada. Huang, Y. J., Su, F., Seo, D., & Krarti, M. (2014). Development of 3012 IWEC2 Weather Files for International Locations (RP-1477). ASHRAE Transactions, 120(1), 340-355. Jentsch, M. F., Bahaj, A. S., & James, P. A. (2008). Climate change future proofing of buildings Generation and assessment of building simulation weather files. Energy and Buildings, 40(12), 2148-2168. SENES Consultants Limited. (2011). Toronto’s Future Weather and Climate Driver Study. Richmond Hill: City of Toronto. UCLA Energy Design Tools Group. (2016). Climate Consultant [Computer Software]. Los Angeles, CA: University of California, Los Angeles. University Corporation for Atmospheric Research. (2016, 12 5). WRF Model Users’ Page. (National Center for Atmospheric Research) Retrieved 12 12, 2016, from http://www2.mmm. ucar.edu/wrf/users/
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