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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Few third-party guidance documents or tools are available for evaluating thermal energy storage (TES) integrated with packaged air conditioning (AC), as this type of TES is relatively new compared to TES integrated with chillers or hot water systems. To address this gap, researchers at the National Renewable Energy Laboratory conducted a project to improve the ability of potential technology adopters to evaluate TES technologies. Major project outcomes included: development of an evaluation framework to describe key metrics, methodologies, and issues to consider when assessing the performance of TES systems integrated with packaged AC; application of multiple concepts from the evaluation framework to analyze performance data from four demonstration sites; and production of a new simulation capability that enables modeling of TES integrated with packaged AC in EnergyPlus. This report includes the evaluation framework and analysis results from the project.
The intent of this user guide is to provide a description of the functionality of the Energy Charting and Metrics plus Building Re-tuning and Measurement and Verification (ECAM+) tool. ECAM+ facilitates the charting and analysis of energy use and point-level data from utility meters, building automation systems (BASs), and data loggers. This document describes the tool’s general functions and features, including installation, use, guidance, and limitations.The Energy Charting and Metrics Tool (ECAM) is an add-on for Microsoft Excel® which was developed to facilitate analysis of data from building (energy and other data). Key features of ECAM+ include the creation of charts to help re-tuning.
This document provides facility managers and building owners with an introduction to measurement and verification (M&V) methods to estimate energy and cost savings of rooftop units replacement or retrofit projects. The M&V methods presented here are helpful in estimating paybacks to justify future projects.
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.
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."