This case study describes the National Renewable Energy Laboratory's (NREL) data center as a showcase of energy efficiency. Most of what NREL has done can be replicated by clients; however, two design approaches are climate-dependent: near-full reliance on outside air for cooling, and photovoltaic arrays for power.
Advanced SearchYour search resulted in 36 resources
This publication details the design, implementation strategies, and continuous performance monitoring of NREL's Research Support Facility data center.
This case study details the design and operations of the National Renewable Energy Laboratory (NREL) Research Support Facility data center and its contributions to energy efficiency.
Commercial Building Partnerships project portrait describing the strategies and technologies used to save 40% over energy code requirements.
InterContinental Hotels Group (IHG) and its franchise partner B.F. Saul Company Hospitality Group (B.F. Saul Co.) partnered with the Department of Energy (DOE) to develop and implement solutions to retrofit existing buildings to reduce energy consumption by at least 30% versus requirements set by Standard 90.1-2004 of the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE), the American National Standards Institute (ANSI), and the Illuminating Engineering Society of North America (IESNA) as part of DOE’s Commercial Building Partnerships (CBP) Program.
An energy-efficient data center includes targets for its power usage effectiveness (<1.2) and energy resource efficiency (< 0.9). It should be designed with hot isle–cold isle separation, use free cooling (economizer) and evaporative cooling when available, minimize fan energy, and use the most energy-efficient equipment possible.
Bank of America partnered with DOE's Commercial Building Partnerships (CBP) Program to develop and implement solutions to build a new bank branch in Punta Gorda, Florida, with a goal of being at least 50% below ASHRAE Standard 90.1-2004. The branch opened in October 2011 and achieved actual energy savings of 47%.
PNC Financial Services partnered with DOE's Commercial Building Partnerships (CBP) Program to develop and implement solutions to retrofit its existing Singer Island, Florida, branch to reduce energy consumption by at least 30% versus ASHRAE Standard 90.1-2004. Construction was completed in January 2012.
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.
This paper will discuss the Building Agent™ platform, which has been developed and deployed in a campus setting at the National Renewable Energy Laboratory. The Building Agent™ provides aggregated and coherent access to building data, including electric energy, thermal energy, temperatures, humidity, and lighting levels, and occupant feedback, which are displayed in various manners for visitors, building occupants, facility managers, and researchers. This paper focuses on the development of visualizations for facility managers, or an energy performance assurance role, where metered data are used to generate models that provide live predicted ranges of building performance by end use.