This publication details the design, implementation strategies, and continuous performance monitoring of NREL's Research Support Facility data center.
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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.
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.
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.
The U.S. General Services Administration (GSA) owns and leases over 354 million square feet (ft2) of space in over 9,600 buildings. GSA is a leader among federal agencies in aggressively pursuing energy efficiency (EE) opportunities for its facilities and installing renewable energy (RE) systems to provide heating, cooling, and power to these facilities. According to several energy assessments of GSA's buildings conducted by the National Renewable Energy Laboratory (NREL), plug-loads account for approximately 21% of the total electricity consumed within a standard GSA Region 3 office building. This study aims to provide insight on how to effectively manage plug-load energy consumption and attain higher energy and cost savings for plug-loads. As GSA improves the efficiency of its building stock, plug-loads will become an even greater portion of its energy footprint.