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Sensitivity analysis identifies how uncertainties in input parameters affect important measures of building performance, such as cost, indoor thermal comfort, or CO2 emissions. Input parameters for buildings fall into roughly three categories:

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  • Sensitivity analysis identifies how uncertainties in input parameters affect important measures of building performance, such as cost, indoor thermal comfort, or CO2 emissions. Input parameters for buildings fall into roughly three categories: * Discrete design alternatives, e.g. different glazing options, number of storeys, etc. * Variance in physical parameters such as U-values, air tightness and location of leakages, and variance/uncertainty in economic parameters such as interest rate, energy prices, or service-life. * Stochastic behaviour-related parameters such as occupancy pattern (number, timing, and location), and use of hot water, window airing, lighting and electrical equipment. Differing personal preferences for air temperature and lighting level. Each parameter has a different distribution of possible values. Sensitivity analysis is an effective way of identifying which parameters influence simulation results the most, and thus need more attention during design. More specifically, sensitivity analysis qualifies how much each parameter affects the results, either individually or in combination (synergistic or antagonistic), and quantifies the variance in possible outcomes, such as energy costs, and is thus a very powerful quantitative tool for decision making. (en)
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  • Sensitivity analysis identifies how uncertainties in input parameters affect important measures of building performance, such as cost, indoor thermal comfort, or CO2 emissions. Input parameters for buildings fall into roughly three categories: (en)
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  • Sensitivity analysis of an EnergyPlus model (en)
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