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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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.
OpenStudio development efforts have been focused on providing Application Programming Interfaces (APIs) where users are able to extend OpenStudio without the need to compile the open source libraries. This paper will discuss the basic purposes and functionalities of the core libraries that have been wrapped with APIs including the Building Model, Results Processing, Advanced Analysis, Uncertainty Quantification, and Data Interoperability through Translators. Several building energy modeling applications have been produced using OpenStudio's API and Software Development Kits (SDK) including the United States Department of Energy's Asset ScoreCalculator, a mobile-based audit tool, an energy design assistance reporting protocol, and a portfolio scale incentive optimization analysis methodology. Each of these software applications will be discussed briefly and will describe how the APIs were leveraged for various uses including high-level modeling, data transformations from detailed building audits, error checking/quality assurance of models, and use of high-performance computing for mass simulations.