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.
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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.
It is still early in the collection and analysis of energy performance data, but it is already clear that high-performance commercial buildings—some "almost net-zero buildings"—can be constructed cost effectively, providing productive environments for occupants, reducing operating costs, and enhancing the competitiveness of commercial properties.