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 article appears in the July 2016 issue of the ASHRAE Journal (pgs. 38-45). Brief summary:
The U.S. Department of Energy's Building Performance Database (BPD) is the largest publicly available data source for energy-related characteristics of commercial and residential buildings in the United States, collected from federal, state, and local governments, utilities, and private companies. The BPD provides anonymized building energy use and asset data with analytical capabilities to help energy service providers, real estate owners and managers, policy makers, and energy consultants make decisions about energy efficiency and retrofit projects.
This article examines some of the promises and perils of having large amounts of building data at the user's fingertips and how to use such data and statistical analysis tools effectively to support decision-making by energy professionals.
This study expands and validates previous research by Heschong Mahone Group that found a statistical correlation between the amount of daylight in elementary school classrooms and student performance. The researchers reanalyzed student performance data from two school districts to answer questions raised by the previous study. The results are consistent with the original findings and affirm that daylight has a positive and highly significant association with improved student performance.
Evidence has shown that owning and operating energy-efficient, high-performance properties is a sound investment strategy that results in multiple financial benefits, including lower utility bills, higher rents, improved occupancy, and greater net operating income (NOI). To overcome difficulties in isolating moderating factors and identifying specific drivers behind sustainability-related improvements in financial performance and value to investors, DOE commissioned this pilot study; designed to test the logistical and empirical procedures required to conduct real estate research and contribute to the existing body of evidence in this field.
In this paper, we apply an automated whole-building M&V tool to historic data sets from energy efficiency programs to begin to explore the accuracy, cost, and time trade-offs between more traditional M&V, and these emerging streamlined methods that use high-resolution energy data and automated computational intelligence. The results show that 70% of the buildings were well suited to the automated approach. In a majority of the cases (80%) savings and uncertainties for each individual building were quantified to levels above the criteria in ASHRAE Guideline 14.
"The general concept of using meter data to quantify building energy savings is intuitive and straightforward; in practice, however, there are many complications. With support from DOE, LBNL has been working with partners to address many of the market and technical barriers for M&V 2.0."
This short blog article describes a related white paper titled "The Status and Promise of Advanced M&V: An Overview of 'M&V 2.0 Methods, Tools, and Applications" and a technical article titled "Application of Automated Measurement and Verification to Utility Energy Efficiency Program Data."
"The objective of this paper is to provide background information and frame key discussion points related to advanced M&V. The paper identifies the benefits, methods, and requirements of advanced M&V and outlines key technical issues for applying these methods. It presents an overview of the distinguishing elements of M&V 2.0 tools and of how the industry is addressing needs for tool testing, consistency, and standardization, and it identifies opportunities for collaboration."
Through the Better Buildings Workforce Guidelines, industry now has national guidelines from which to develop high quality and nationally recognized training and certification programs, helping to address challenges found in the energy efficiency workforce with quality, consistency, and scalability across certification and certificate programs.
The Department of Energy worked with the National Institute of Building Sciences (NIBS) and industry stakeholders to develop the Better Buildings Workforce Guidelines, voluntary national guidelines to improve the quality and consistency of commercial building workforce credentials for four key energy-related jobs: Building Energy Auditor, Building Commissioning Professional, Building Operations Professional, Energy Manager.
The Better Buildings Workforce Guidelines aligns all elements of the Better Buildings Workforce Framework, with the goal of supporting high-quality industry and government-recognized credentials for 4 key commercial energy-related job titles. Together, the Job Task Analyses (JTA) documents and the certification schemes comprise the content of the voluntary, industry-developed, and industry and government-recognized Better Buildings Workforce Guidelines.