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Heather Burpee with the University of Washington's Integrated Design Lab reviewed an earlier draft of this report.The authors extend their thanks to their NREL colleagues Kyle Benne and Michael Sheppy for conducting formal internal reviews of this document, and to Stefanie Woodward and Sara Havig for providing editing assistance.Thousands of EnergyPlus simulations were run to fully debug and finalize the energy models referenced by this report. This would not have been possible without the support of the NREL High Performance Computing Center managed by Jim Albin and Wesley Jones. Additional thanks go to Torri Lopez of the NREL High Performance Computing Center for helping to install and maintain the software necessary to perform energy simulations on the Windows High Performance Computing cluster.Finally, several other NREL colleagues provided valuable guidance and information during the modeling process, either directly or through their past work. Ian Doebber contributed insights, particularly heating, ventilation, and air conditioning insights, gained through his work on previous healthcare projects. Jennifer Scheib provided electric lighting data. Kyle Benne provided programming and automation assistance, and Brent Griffith contributed invaluable EnergyPlus modeling and debugging assistance.ii Executive SummaryThe Commercial Buildings Group at NREL developed this Technical Support Document under the direction of the U.S. Department of Energy Building Technologies Program. It documents the technical analysis performed and the resulting design guidance that will enable large hospitals to achieve whole-building energy savings of at least 50% over ANSI/ASHRAE/IESNA Standard 90.1-2004. This report also documents in detail the modeling methods used to demonstrate that the design recommendations meet or exceed the 50% energy savings goal. MethodologyTo account for energy interactions between building subsystems, we used EnergyPlus (DOE 2010) to model the predicted energy performance of the baseline and low-energy buildings to verify that 50% energy savings are achievable in all climate zones. EnergyPlus computes building energy use based on the interactions between climate, building form and fabric, internal gains, and heating, ventilating, and air conditioning systems. The percent energy savings values presented in this document are based on a nominal minimally code-compliant building, as described in Standard 90.1-2004, and utilize a whole-building site energy use intensity metric (Torcellini et al. 2006).The following steps were used to determine 50% savings:1. Define architectural-program characteristics (design features not addressed by Standard 90.1-2004) for a typical large hospital, thereby defining a single prototype model. 2. Create baseline energy models for each climate zone that are elaborations of the prototype model and are compliant with Standard 90.1-2004, using industry feedback to strengthen the inputs for the baseline models. 3. Create low-energy models for each climate zone by applying a list...

Recent efforts to reduce energy consumption and greenhouse gas emissions have resulted in the development of sustainable, smart districts with highly energy efficient buildings, renewable distributed energy resources (DERs), and support for alternative modes of transportation. However, there is typically little if any coordination between the district developers and the local utility. Most attention is paid to the district's annual net load and generation without considering their instantaneous imbalance or the connecting network's state. This presents an opportunity to learn lessons from the design of distribution feeders for districts characterized by low loads and high penetrations of DERs that can be applied to the distribution grid at large. The aim of this overview is to summarize current practices in sustainable district planning as well as advances in modeling and design tools for incorporating the power distribution system into the district planning process. Recent developments in the modeling and optimization of district power systems, including their coordination with multi-energy systems and the impact of high penetration levels of renewable energy, are introduced. Sustainable districts in England and Japan are reviewed as case studies to illustrate the extent to which distribution system planning has been considered in practice. Finally, newly developed building-to-grid modeling tools that can facilitate coordinated district and power system design with utility involvement are introduced, along with suggestions for future research directions.

This report is one in a series of Electrification Futures Study (EFS) publications. The EFS is a multi-year research project to explore widespread electrification in the future energy system of the United States. This report documents a new model, the demand-side grid (dsgrid) model, which was developed for the EFS and in recognition of a general need for a more detailed understanding of electricity load. dsgrid utilizes a suite of bottom-up engineering models across all major economic sectors-transportation, residential and commercial buildings, and industry-to develop hourly electricity consumption profiles for every county in the contiguous United States (CONUS). The consumption profiles are available by subsector and end use as well as in aggregate. This report documents a bottom-up modeling assessment of historical ( 2012) consumption and explains the key inputs, methodology, assumptions, and limitations of dsgrid.The EFS is specifically designed to examine electric technology cost advancement and adoption for end uses across all major economic sectors as well as electricity consumption growth and load profiles, future power system infrastructure development and operations, and the economic and environmental implications of electrification. Because of the expansive scope and the multiyear duration of the study, research findings and supporting data will be published as a series of reports, with each report released on its own timeframe. Future research to be presented in future planned EFS publications will rely on dsgrid to analyze the hourly electricity consumption under scenarios with various levels of electrification. In addition to providing electricity consumption data for the planned EFS analysis, dsgrid can be used for other analysis outside the EFS research umbrella.More information and the supporting data associated with this report, links to other reports in the EFS study, and information about the broader study are available at www.nrel.gov/efs.