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Abstract Convenience stores are known to have higher Energy Use Intensities (EUIs) than most other commercial building types. However, convenience store energy performance analyses have not been systematically investigated. Moreover, current national convenience store benchmarks are inconsistent from one data base to another due to lack of relevant energy data. This paper assesses the energy performance of more than five hundred convenience stores in the same fleet in Eastern United States. The investigation aims to establish benchmarks for convenience stores with and without gasoline pumping stations. The main factors influencing the actual convenience store building energy use were determined. Multiple regression models were developed to find relationships between annual energy consumption per unit area and gross floor area, customer transaction count, building operating year, etc. The statistically characterized results are meant to serve as a reference data set in comparing the whole-building energy performance index for buildings of similar functionality. The statistical correlation analyses can strengthen the robust prediction of energy performance in convenience stores, enabling proper assessment of energy conservation measurements (ECMs) for convenience store operations, as well as guiding additional such energy performance studies. [ABSTRACT FROM AUTHOR]

Abstract: The energy performance of buildings has become increasingly important in the general strive to reduce the overall energy use, which is manifested in the Energy Performance of Buildings Directive launched by the European Union. An important first step is of course to identify and address buildings that have an energy saving potential. In order to achieve this, robust methods for evaluation as well as reliable energy key figures are needed. For a large majority of multifamily buildings in Sweden the available data of the energy use originates from the property holder. Unfortunately, the data is often limited to the energy that the property holder is responsible for. Thus, information from the tenants about their household electricity use, indoor temperatures, number of residents, etc., is missing. In this paper an evaluation was conducted on monthly consumption data registered by the property holders for over 100 multifamily buildings/real estates in Sweden. The used approach, based on the energy signature method, was developed for evaluating the energy performance of multifamily buildings in terms of the overall heat loss coefficient, K tot. To compensate for the missing data, different assumed consumption profiles have been used. The results shows that although the obtained value of K tot for an individual building is rather sensitive to the assumed consumption profiles of household electricity, the sensitivity is reduced if the evaluation is made in relative and not absolute terms. Thus, the use of consumption profiles could be a successful way to circumvent the present lack of a detailed knowledge of a buildings total energy use. In addition, an evaluation in relative terms instead of absolute values is also more correct, since available data in almost all cases does not support the determination of the true value of K tot. The use of an average consumption profile instead of a detailed knowledge is of course not desirable, but for fairly large buildings such an approach could be successful. [Copyright &y& Elsevier]