This Fact Sheet provides an overview of the Better Buildings Workforce Guidelines project. The Department of Energy (DOE) and the National Institute of Building Sciences (NIBS) are working with industry stakeholders to develop voluntary national guidelines that will improve the quality and consistency of commercial building workforce training and certification programs for five key energy-related jobs.
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The lack of empirical data on the energy performance of buildings is a key barrier to accelerating the energy efficiency retrofit market. The DOE’s Buildings Performance Database (BPD) helps address this gap by allowing users to perform exploratory analyses on an anonymous dataset of hundreds of thousands of commercial and residential buildings. These analyses enable market actors to assess energy efficiency opportunities, forecast project performance, and quantify performance risk using empirical building data. In this paper, we describe the process of collecting and preparing data for the database, and present a peer-group analysis tool that allows users to analyze building performance for narrowly defined subsets of the database, or peer groups. We use this tool to explore a case study of a multifamily portfolio owner comparing his buildings’ performance to the peer group of multifamily buildings in the local metro area. We also present a performance comparison tool that uses statistical methods to estimate the expected change in energy performance due to changes in building-component technologies. We demonstrate a low-effort retrofit analysis, providing a probabilistic estimate of energy savings for a sample building retrofit. The key advantages of this approach compared to conventional engineering models are that it provides probabilistic risk analysis based on actual
measured data and can significantly reduce transaction costs for predicting savings across a portfolio.
This project focuses on testing and demonstrating both the hardware and Cloud versions of theSMDS under field conditions. The objectives for testing and demonstrating the hardware are to 1) characterize the performance of the SMDS technology, 2) estimate the savings-to-cost ratio for demonstration units, and 3) characterize the usability of the SMDS including ease of installation and use. The SMDS provides information to the user, but to realize savings, actions must be taken by the user. The hardware demonstrations seek to discover how effective information is in influencing actions, including which faults generate the most servicing actions by the user.
These field demonstrations are of prototype SMDS units, which have not yet completed the product development process. These early demonstration projects are critical to understanding SMDS performance in the field and to gaining a better understanding of the potential performance or user interface enhancements needed in the next generation SMDS units. Conclusions related to the larger commercial building market, such as the incidence of performance degradation and specific faults and the energy savings resulting from addressing them are beyond the scope of this study and not compatible with the current stage of SMDS development.
The demonstration was performed separately for the hardware and Cloud versions of the SMDS. Both demonstrations involved selecting buildings, installing the required hardware (although it requires less hardware, the Cloud version requires sensors and cell modems), collecting and processing data, and viewing and tabulating results. Details of the procedures are presented later in this report.