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The ENERGY STAR Portfolio Manager Data Explorer houses energy data for over 150,000 U.S. commercial, multifamily, and single-family properties. The Data Explorer allows users to query this data and explore energy metrics such as Energy Use Intensity (EUI), ENERGY STAR Score, and Percent Electricity across a wide range of property types and characteristics. A variety of filters and metric display options provide customizable results. The tool is available at https://portfoliomanager.energystar.gov/dataExplorer.
The ENERGY STAR Score for K-12 Schools applies to buildings or campuses used as a school for kindergarten through 12th grade students. The objective of the ENERGY STAR score is to provide a fair assessment of the energy performance of a property relative to its peers, taking into account the climate, weather, and business activities at the property. To identify the aspects of building activity that are significant drivers of energy use and then normalize for those factors, a statistical analysis of the peer building population is performed.
This document presents details on the development of the 1 – 100 ENERGY STAR Score for vehicle dealerships, which applies to buildings used for the sale of new or used light-, medium- and heavy-duty cars and trucks. The objective of the ENERGY STAR score is to provide a fair assessment of the energy performance of a property relative to its peers, considering the climate, weather, and business activities at the property.
This Excel spreadsheet contains historical emissions factors dating back to 2000. Use this as a reference to understand which historical factors are being applied to your buildings' emissions.
The 1 – 100 ENERGY STAR score for Single-Family Homes applies to single-family detached and attached homes. The objective of the ENERGY STAR score is to provide a fair assessment of the energy performance of a property relative to its peers, taking into account the climate, weather, and activities at the property. To identify the aspects of building activity that are significant drivers of energy use and then normalize for those factors, a statistical analysis of the peer building population is performed.