Effects of sub-optimal component performance on overall cooling system energy consumption and efficiency
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Predicted cooling system performance plays an important role in choices among alternative system selections and designs. When system performance is expressed in proper indicators such as "overall system energy consumption" or "overall system efficiency", it can provide the decision makers with a quantitative measure of the extent to which a cooling system satisfies the system design requirements and objectives. Predictions of cooling system energy consumption and efficiency imply assumptions about component performance. Quantitative appraisal of the uncertainty (lack of knowledge) in these assumptions can be used by design practitioners to select and design systems, by energy contractors to guarantee future system energy cost savings, and codes and standards officials to set proper goals to conserve energy. Our lack of knowledge has different sources, notably unknown tolerances in equipment nameplate data, and unpredictable load profiles. Both cause systems to under-perform current predictions, and as a result decrease the accuracy of the outcomes of energy simulations that commonly are used to verify system performance during the design and construction stages. There can be many other causes of unpredictable system behavior, for example due to bad workmanship in the installation, occurrence of faults in the operation of certain system parts, deterioration over time and other. These uncertainties are typically much harder to quantify and their propagation into the calculated energy consumption is much harder to accomplish. In this thesis, these categories of failures are not considered, i.e. the treatment is limited to component tolerances and load variability. In this research the effects of equipment nameplate tolerances and cooling load profile variability on the overall energy consumption and efficiency of commonly used commercial cooling systems are quantified. The main target of this thesis is to present a methodology for calculating the chances that a specific cooling system could deviate from a certain efficiency level by a certain margin, and use these results to guide practitioners and energy performance contractors to select, and guarantee system performances more realistically. By doing that, the plan is to establish a systematic approach of developing expressions of risk, in commercial cooling system consumption and efficiency calculations, and thus to advocate the use of expressions of risk as design targets. This thesis makes a contribution to improving our fundamental understanding of performance risk in selecting and sizing certain HVAC design concepts.