Large-scale assessments of the vulnerability of electric infrastructure are usually performed for a baseline water year or a specific period of drought. This approach does not provide insights into the full distribution of stress on the grid across the diversity of historic climate events. In this paper we estimate the Western US grid stress distribution as a function of inter-annual variability in regional water availability. We softly couple an integrated water model (climate, hydrology, routing, water resources management, and socioeconomic water demand models) into an electricity production cost model and simulate electricity generation and delivery of power for combinations of 30 years of historical water availability data. Results indicate a clear correlation between grid vulnerability (unmet electricity services) for the month of August, and annual water availability. There is a 21% chance of insufficient generation (system threshold) and a 3% chance that at least 6% of the electricity demand cannot be met in August. Better knowledge of the probability distribution of the risk exposure of the electricity system due to water constraints could improve power system planning. Deeper understanding of the impacts of regional variability in water availability on the reliability of the grid could help develop tradeoff strategies.

This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the EIC (Eastern Interconnection) located in the United States. The climate change scenario considered includes changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. Simulations were performed using the BEND (Building ENergy Demand) model which is a detailed building analysis platform utilizing EnergyPlus™ as the simulation engine. Over 26,000 building configurations of different types, sizes, vintages, and characteristics representing the population of buildings within the EIC, are modeled across the three EIC time zones using the future climate from 100 target region locations, resulting in nearly 180,000 spatially relevant simulated demand profiles for three years selected to be representative of the general climate trend over the century. This approach provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability to perform detailed hourly impact studies of building adaptation and mitigation strategies on energy use and electricity peak demand within the context of the entire grid and economy.

Objective: Because long-term socioeconomic transformation and energy service expansion show large spatial heterogeneity, advanced understanding of climate change impact on buildings energy use at the sub-national level will offer useful insights into climate policy and regional energy system planning.Methods: In this study, we present a detailed buildings energy model with U.S. state-level representation, nested in an integrated assessment framework of the Global Change Assessment Model (GCAM). We project state-level buildings energy demand and its spatial pattern through the end of the century, considering the impact of climate change based on the estimates of heating and cooling degree days derived from downscaled USGS CASCaDE temperature data.Results: The results indicate that climate change has a large impact on heating and cooling buildings energy and fuel use at the state level and that the 48 U.S. contiguous states exhibit a large spatial heterogeneity (ranges from -10% to +10% for total, -10% to +20% for electricity use and -20% to -5% for oil and gas use in the A2 scenario). Sensitivity analysis explores the potential implications of multiple driving forces, including climate action that would both change the price of energy and reduce climate change, the choice of climate models, and population and GDP growth. In addition, the 50-state building model is compared to a comparable version of the model which represents the entire United States as one region.Conclusions: The study clearly demonstrates the spatially varying nature of fuel consumption changes that might occur from a changing climate. Although the study illustrates the importance of incorporating climate change into infrastructure-planning exercises, it also demonstrates that uncertainties about underlying drivers still must weigh heavily on these planning decisions. Finally, the study demonstrates that the 50-state building model provides both insights at the regional level and potentially better national-level estimates.Practice implication: The findings from this study will help the climate-based policy decision and energy system, especially utility planning related to the buildings sector at the U.S. state and regional level facing the potential climate change. C) 2013 Elsevier Ltd. All rights reserved.

Modern workflow systems can enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve. However as a result of these new capabilities the science teams suddenly also face unprecedented data volumes that they are unable to analyze with their existing tools and methodologies in a timely fashion. In this paper we describe the ongoing development work to create an integrated data intensive scientific workflow and analysis environment that offers researchers the ability to easily create and execute complex simulation studies and provides them with different scalable methods to analyze the resulting data volumes. The capabilities of the new environment are demonstrated on a use case that focuses on building energy modeling. As part of the PNNL research initiative PRIMA (Platform for Regional Integrated Modeling and Analysis) the team performed an initial 3-year study of building energy demands for the US Eastern Interconnect domain. They are now planning to extend to predict the demand for the complete century. In the 3-year study the team simulated 2000 individual building types for 100 independent climate similar regions (600 000 individual runs) raising their data demands from a few MBs to 400 GB for the 3-year study.

As the relationship between the national building stock and various global energy issues becomes a greater concern, it has been deemed necessary to develop a system of predicting the energy consumption of large groups of buildings. Ideally this system is to take advantage of the most advanced energy simulation software available, be able to execute runs quickly, and provide concise and useful results at a level of detail that meets the users needs without inundating them with data. The resulting methodology that was developed allows the user to quickly develop and execute energy simulations of many buildings simultaneously, taking advantage of parallel processing to greatly reduce total simulation times. The result of these simulations can then be rapidly condensed and presented in a useful and intuitive manner.

The U.S. Department of Energy (DOE) recently initiated a program -- Commercial Building Partnerships (CBP) -- to work with private-sector companies in the design of highly-efficient retrofit and new construction projects. Pacific Northwest National Laboratory (PNNL) is conducting a project with a major hotel company to retrofit a full-service, large hotel with the goal of reducing energy consumption by at least 30%. The first step of the project was an intensive metering and monitoring effort aimed at understanding energy end use patterns in the hotel. About 10% of the guest rooms (32), as well as circuits for most of the end uses in public spaces (lighting, elevators, air handlers and other HVAC system components, and various equipment), were equipped with meters. Data are being collected at 1- or 5-minute intervals and downloaded on a monthly basis for analysis. This paper presents results from the first four months of the monitoring effort, which revealed energy end-use consumption patterns, variability of guest room energy use, daily load curves, monthly variations, and other aspects of hotel energy use. Metered end-use data for hotels at this level of detail are not available from any currently-available public sources. This study presents unique information and insightmore » into energy end-use patterns in the lodging sector of commercial buildings and can also serve as a case study of a complex sub-metering project.« less

This report examines the factors that would potentially help determine an appropriate analytical timeframe for measuring the U.S. Department of Energy's Building Technology (BT) benefits and presents a summary-level analysis of the life cycle savings for BT’s Commercial Buildings Integration (CBI) R&D program. The energy savings for three hypothetical building designs are projected over a 100-year period using Building Energy Analysis and Modeling System (BEAMS) to illustrate the resulting energy and carbon savings associated with the hypothetical aging buildings. The report identifies the tasks required to develop a long-term analytical and modeling framework, and discusses the potential analytical gains and losses by extending an analysis into the “long-term.”

This report summarizes the results and the assumptions used in an analysis of the potential “lost efficiency opportunities” in the buildings sector. These targets of opportunity are those end-uses, applications, practices, and portions of the buildings market which are not currently being addressed, or addressed fully, by the Building Technologies Program (BTP) due to lack of resources. The lost opportunities, while a significant increase in effort and impact in the buildings sector, still represent only a small portion of the full technical potential for energy efficiency in buildings.

US residential and commercial buildings were responsible for about 41 exajoules (EJ) of primary energy use per year in 2002, accounting for approximately 9% of the world fossil-fuel related anthropogenic carbon (C) emissions of 6.7 Gt that contribute to climate change. US Government-sponsored building energy efficiency research and implementation programs are focused on reducing energy consumption in US residential and commercial buildings and reducing these carbon (C) emissions. Although not specifically intended for adaptation to a warmer climate and less effective than under today’s cooler climate, these programs also could help reduce energy demand in a future warmer world. Warming scenarios projected by the United Nations Intergovernmental Panel on Climate Change (IPCC) in 2001 imply net overall decreases in both site energy and primary energy consumption in US residential and commercial buildings, largely because of the reduced need for heating. However, there would be as much as a 25% increase in building space cooling demand and a significant part of the increase could be offset by energy-efficiency improvements in buildings. Overall, in the US, buildings-related energy efficiency programs would reduce site energy consumption in buildings in the US by more than 2 EJ in 2020 and primary energy by more than 3.5 EJ, more than enough to offset the projected growth in cooling energy consumption due to climate change and growth in the US building stock. The savings would have an estimated annual net value at 2005 energy prices of between $45.0 and $47.3 billion to consumers.

The Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) is interested in assessing the potential economic impacts of its portfolio of subprograms on national employment and income. A special purpose version of the IMPLAN input-output model called ImBuild II is used in this study of 20 subprograms of the Weatherization and Intergovernmental Program contained in the EERE final FY 2005 budget request to the Office of Management and Budget on February 2, 2004. Energy savings, investments, and impacts on U.S. national employment and earned income are reported by subprogram for selected years to the year 2030. Energy savings and investments from these subprograms have the potential of creating a total of 228,000 jobs and about $3.1 billion in earned income (2003$) by the year 2030.

The requirements of the Government Performance and Results Act (GPRA) of 1993 mandate the reporting of outcomes expected to result from programs of the Federal government. The U.S. Department of Energy’s (DOE’s) Office of Energy Efficiency and Renewable Energy (EERE) develops official metrics for its 11 major programs using its Office of Planning, Budget Formulation, and Analysis (OPBFA). OPBFA conducts an annual integrated modeling analysis to produce estimates of the energy, environmental, and financial benefits expected from EERE’s budget request. Two of EERE’s major programs include the Building Technologies Program (BT) and Office of Weatherization and Intergovernmental Program (WIP). Pacific Northwest National Laboratory (PNNL) supports the OPBFA effort by developing the program characterizations and other market information affecting these programs that is necessary to provide input to the EERE integrated modeling analysis. Throughout the report we refer to these programs as “buildings-related” programs, because the approach is not limited in application to BT or WIP. To adequately support OPBFA in the development of official GPRA metrics, PNNL communicates with the various activities and projects in BT and WIP to determine how best to characterize their activities planned for the upcoming budget request. PNNL then analyzes these projects to determine whatmore » the results of the characterizations would imply for energy markets, technology markets, and consumer behavior. This is accomplished by developing nonintegrated estimates of energy, environmental, and financial benefits (i.e., outcomes) of the technologies and practices expected to result from the budget request. These characterizations and nonintegrated modeling results are provided to OPBFA as inputs to the official benefits estimates developed for the Federal Budget. This report documents the approach and methodology used to estimate future energy, environmental, and financial benefits produced by technologies and practices supported by BT and by WIP. However, the approach is general enough for analysis of buildings-related technologies, independent of any specific program. An overview describes the GPRA process and the models used to estimate energy savings. The body of the document describes the algorithms used and the diffusion curve estimates.« less

The Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) is interested in assessing the potential economic impacts of its portfolio of subprograms on national employment and income. A special purpose version of the IMPLAN input-output model called ImBuild II is used in this study of all 21 Building Technologies Program subprograms in the EERE final FY 2005 budget request to the Office of Management and Budget on February 2, 2004. Energy savings, investments, and impacts on U.S. national employment and earned income are reported by subprogram for selected years to the year 2030. Energy savings and investments from these subprograms have the potential of creating a total of 396,000 jobs and about $5.6 billion in earned income (2003$) by the year 2030.

Previous studies have forecasted the future benefits associated with the Department of Energy's (DOE's) Office of Energy Efficiency and Renewable Energy (EERE) programs. These studies have focused on the impacts of programmatic activities given expected economic and budget situations, and an assumption of complete success. These benefits have invariably been represented as a point estimate, or series of point estimates through time. As the government climate evolves to one with a greater emphasis on portfolio management, it is anticipated that traditional benefits analysis will evolve to a more ex ante decisional activity that will integrate portfolio analysis and program planning with impact analysis and Government Performance and Results Act (GPRA) compliance. A consideration of the uncertainty associated with point estimates of program impacts will almost certainly alter the representation and consideration of this portfolio. Further, R&D decision makers need to be able to look at alternative assumptions of future markets and performance of future technologies in order to gain a better understanding of the range of potential impacts of the R&D portfolio. Comparisons with past benefits analyses have illustrated that changes in assumptions such as proposed technology cost, performance, and size of potential market can significantly affect the benefits forecast.more » This study proposes a new framework for incorporating alternative scenarios into a portfolio tool that provides resulting energy savings estimates given changes from reference-case conditions. The framework can be changed by altering factors such as the R&D budget response functions, alternative macro assumptions (fuel prices, GDP growth, etc.), programmatic interaction scenarios (leveraging efforts, etc), alternative market outlooks (floorspace growth, etc), and alternative program objectives.« less