Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ENERGY MODELS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Wave Energy Converter Modeling

Wave Energy Converter Modeling presentation from the Water Power Technologies Office Peer Review, FY14-FY16. WECs are typically made up of multiple bodies and are designed to maximize their relative motion at dominant sea states (as resonant devices), resulting in complex nonlinear hydrodynamics, particularly during extreme sea states.

13 HYDRO ENERGY↗
DOE OSTI2016

ReEDS™ 2.0 Model (Regional Energy Deployment System Model) Version 2.0 [SWR-20-36 and SWR-09-14]

ReEDS™ is a capacity planning and dispatch model for the U.S. electricity system. As the National Laboratory of the Rockies (NLR's) flagship long-term power sector model, ReEDS has served as the primary analytic tool for many studies of electricity sector research questions. Example model results are available in the Scenario Viewer here: https://scenarioviewer.nlr.gov/. Quick-start guide The ReEDS model is written in Python, GAMS, and Julia. Python and Julia are free, open-source languages; GAMS requires a software license from the vendor. A step-by-step guide for getting started with ReEDS is available here: https://pages.github.nrel.gov/ReEDS/ReEDS-2.0/setup.html.

Short, Walter↗
DOE OSTI2014

Energy savings modelling of re-tuning energy conservation measures in large office buildings

Today, many large commercial buildings use sophisticated building automation systems (BASs) to manage a wide range of building equipment. While the capabilities of BASs have increased over time, many buildings still do not fully use the BAS’s capabilities and are not properly commissioned, operated or maintained, which leads to inefficient operation, increased energy use, and reduced lifetimes of the equipment. This paper investigates the energy savings potential of several common HVAC system re-tuning measures on a typical large office building, using the Department of Energy’s building energy modeling software, EnergyPlus. The baseline prototype model uses roughly as much energy as an average large office building in existing building stock, but does not utilize any re-tuning measures. Individual re-tuning measures simulated against this baseline include automatic schedule adjustments, damper minimum flow adjustments, thermostat adjustments, as well as dynamic resets (set points that change continuously with building and/or outdoor conditions) to static pressure, supply-air temperature, condenser water temperature, chilled and hot water temperature, and chilled and hot water differential pressure set points. Six combinations of these individual measures have been formulated – each designed to conform to limitations to implementation of certain individual measures that might exist in typical buildings. All the individual measures and combinations were simulated in 16 climate locations representative of specific U.S. climate zones. The modeling results suggest that the most effective energy savings measures are those that affect the demand-side of the building (air-systems and schedules). Many of the demand-side individual measures were capable of reducing annual total HVAC system energy consumption by over 20% in most cities that were modeled. Supply side measures affecting HVAC plant conditions were only modestly successful (less than 5% annual HVAC energy savings for most cities for all measures). Combining many of the re-tuning measures revealed deep savings potential. Some of the more aggressive combinations revealed 35-75% reductions in annual HVAC energy consumption, depending on climate and building vintage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

URBANopt (Urban Renewable Building And Neighborhood Optimization) [SWR-16-33]

URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as “what if 30% of the commercial retail buildings added roof top solar” or “what if all elementary schools converted to ground source heat pumps” and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).

Source record↗
DOE OSTI2016

Urban Renewable Building And Neighborhood Optimization

URBANopt is a user interface for creating and running district and city scale building energy simulations. The framework is built around the OpenStudio Urban Measures which are part of the OpenStudio project. Building footprints, building height, building type, and other data can be imported from public records or other sources. Footprints and locations for new buildings and district systems can also be specified. OpenStudio Measures are used to create starting point energy models and to model energy design features and efficiency measures for each building. URBANopt allows a user to pose several scenarios such as “what if 30% of the commercial retail buildings added roof top solar” or “what if all elementary schools converted to ground source heat pumps” and then visualize the impacts at a district or city scale. URBANopt is capable of modeling existing buildings, new construction, and district energy systems. URBANopt can be used to explore options for achieving Zero Energy across a collection of buildings (e.g., Zero Energy Districts).

Source record↗
DOE OSTI2015

Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling & Simulation (Phase I Final Report)

Today, the importance of nuclear power in the US is a geopolitical matter as much as it is an economic one. This is due to the notion that increasing the use of nuclear power reduces the US's reliance on imported oil and gas. In order to design future systems and continue operational improvements at existing US plants, advanced modeling and simulation of nuclear power reactors is crucial. A variety of challenges exist to using advanced modeling and simulation in practice, especially for the nuclear energy community and other organizations with fewer computational resources and limited expertise. There is an increasing need of access to highly capable compute, data, and software resources from network systems, which are becoming more administratively restricted from access through installation of traditional client-server applications. The nuclear energy community is not capable of maintaining exponential growth of computing capability and data storage coupled with the necessary end-to-end network bandwidth improvements. Applications that provide higher fidelity with increased physics and decreased assumptions, by their very nature, require more and more computational resources. We believe Web-based, Cloud-enabled, end-to-end simulation software for nuclear energy advanced modeling and simulation to be the solution to these challenges.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Good practices for documenting AI-based studies on energy and buildings

Artificial intelligence has transformed building science research over the past decade, with applications spanning energy modeling, energy prediction, HVAC optimization and controls, fault detection, and occupancy modeling. However, many studies lack adequate documentation of datasets, algorithms, training procedures, and validation methods. Building science research faces additional challenges including inconsistent evaluation metrics, limited generalizability across building types, climates, and significant gaps between experimental studies and deployed systems. This communication provides practical guidance for good practices in documenting and publishing AI-based research following established standards from the computer science and machine learning communities. By adopting frameworks such as Datasheets for Datasets, Model Cards, and standardized reproducibility checklists, researchers can ensure their work meets the rigorous documentation standards necessary for reproducible, comparable, and impactful building science research.

Hong, Tianzhen [Lawrence Berkeley National Laborat↗
DOE OSTI2024

CAD-based Energy & Cost Models Prove Affordable Net Zero Energy Performance for WonderWindows + 24" On-center Framing

Windows are thermally the “weakest link” in the building envelope. Increasing the thermal resistance of windows can make buildings more energy efficient and reduce the cost of electricity needed for conditioning the building. The proper design and placement of framing can also help to reduce the thermal bridging that occurs near the window frame area. This study investigates the energy performance of multi-pane acrylic windows fitting 24" on-center framing. Initial parametric analysis is done for a single zone accessory dwelling unit (ADU). Then, an energy model was developed for three types of wood-framed buildings: townhomes, stacked flats and hotels. A whole building energy simulation is performed for each of these building types in hot-humid Houston, mixed-humid New York, and cold-humid Minneapolis climates. The results show up to a 39% reduction in heating, ventilation, and air-conditioning (HVAC) related electricity consumption for the cold climate compared to the Base case which has window and wall properties based on ASHRAE standard 90.1 2019. In the hot climate, a modest increase in electricity consumption was seen due to an increase in cooling electricity demand. The ADU achieved Net Zero Energy performance in all 3 Climate Zones despite having the highest exterior surface area-to-floor area ratio: the ADU also had the highest PV kW to floor area ratio compared to the other multi-story building types. The townhomes, hotel and stacked flats respectively met 73, 52 and 57 % of electrical use in Houston, 71, 48 and 56 % in New York, and 63, 40 and 53 % in Minneapolis from energy produced by rooftop solar. If 400 W solar panels are used instead of 320 W panel used for energy simulation, it is estimated that in the townhomes, hotel and stacked flats rooftop solar can meet 91, 65 and 71 % of electrical use in Houston; 89, 60 and 70% in New York, and 79, 50 and 66 % in Minneapolis. A preliminary evaluation of cost shows that such superior performance can potentially be achieved at less first cost with this 24"on-center solution than conventional construction. All the building types at the three locations used for simulation had net energy use intensity under 20 kBtu/sf/year with 320 W solar panel and under 17 kBtu/sf/year with 400 W solar panel. Further tailoring of building envelope R-values and window solar heat gain to particular Climate Zone locations for each building type shows promise in reducing the HVAC electricity use that comprises almost half of building energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Comparative Study of Enhanced Geothermal System Supply Curves Across CONUS from Two Temperature Models Using the Renewable Energy Potential Model (reV)

Enhanced geothermal systems (EGS) have had recent breakthroughs within the geothermal sector. These breakthroughs are reflected in the National Renewable Energy Laboratory (NREL) 2024 Annual Technology Baseline and will result in updated EGS supply curves (i.e., the available resource capacity relative to cost). Our research uses NREL's Renewable Energy Potential (reV) model to compare EGS supply curves across the conterminous United States (CONUS) for two different temperature models: the Stanford temperature model (STM) and the Southern Methodist University temperature model (SMU). The reV model provides the levelized cost of energy (LCOE) at a consistent resolution across CONUS, taking into consideration transmission costs and constraints as well as technical exclusions pertaining to sensitive cultural, ecological, or infrastructure locations. In addition to a countrywide analysis of both models, we also conducted a regional analysis of Texas. We observed the STM had, on average, lower temperatures across different depths, resulting in slightly higher mean and median LCOEs as compared to the SMU temperature model at the same depths. In the regional analysis for Texas, however, when we compared only the common points between the two temperature models, the STM had lower median and mean LCOEs compared to SMU due to higher temperatures at depths greater than 5 km.

enhanced geothermal systems↗
DOE OSTI2017

Web-Based Computational Model Builder For Nuclear Energy Advanced Modeling and Simulation (Final Report)

According to the World Nuclear Association, the U.S. is the largest producer of nuclear power worldwide. In fact, the U.S. provides over 30 percent of the world's nuclear generation of electricity. Although few new reactors have been built in the past 30 years, the association anticipates that four to six reactors may be built by 2020. The first of the reactors will be built in response to 16 license applications, which have been completed since 2007, to build 24 additional nuclear reactors. Currently, both government and industry are working to accelerate approval for the construction and design of new nuclear energy plants. The U.S. nuclear industry has already achieved significant developments in the implementation of nuclear power plants due to advancements in refueling, maintenance, and safety systems at current power plants. Meanwhile, changes in government policy, which have occurred since the late 1990s, have provided for noteworthy expansion in nuclear capacity. For example, the Energy Policy Act of 2005 evoked investment in electricity infrastructure such as nuclear power. To design future systems and continue operational improvements at existing U.S. plants, advanced modeling and simulation of nuclear reactors are crucial. We developed a Cloud/Web-based tool, HPCCloud, that enables nuclear energy firms, or other manufacturing and engineering companies, to innovate using advanced modeling and simulation. Through the Web-Based Computational Model Builder for Nuclear Energy Advanced Modeling and Simulation grant, we develop HPCCloud to simplify and democratize advanced modeling and simulation in the nuclear energy industry on a range of nuclear engineering applications. It leverages millions of investment dollars from the Department of Energy's Consortium for Advanced Simulation of Light Water Reactors (CASL) and the Office of Nuclear Energy's research and development in Nuclear Energy Advanced Modeling and Simulation (NEAMS). Our approach simplifies the workflow, alleviates the need for in-house computational science and engineering experts, and lowers the capital investments required for advanced modeling and simulation. The Cloud/Web-based simulation environment guides end-users and developers through the advanced modeling and simulation lifecycle. In addition to providing significantly improved, intuitive software, the environment offers reproducible workflows where one can save, share, and even publish the full path of data from input to final analyzed results. HPCCloud addresses identified challenges to the nuclear energy industry's use of advanced modeling and simulation. With this unique Cloud/Web-based environment, we enable an ecosystem of synergistic activities, fueling new research and development for nuclear energy. HPCCloud lays the groundwork for commercialization, through customization, technology integration, and advanced research and development services.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

The observational constraints on the flat $\phi $CDM models

Most dark energy models have the Λ CDM as their limit, and if future observations constrain our universe to be close to Λ CDM Bayesian arguments about the evidence and the fine-tuning will have to be employed to discriminate between the models. Assuming a baseline Λ CDM model we investigate a number of quintessence and phantom dark energy models, and we study how they would perform when compared to observational data, such as the expansion rate, the angular distance, and the growth rate measurements, from the upcoming Dark Energy Spectroscopic Instrument (DESI) survey. We sample posterior likelihood surfaces of these dark energy models with Monte Carlo Markov Chains while using central values consistent with the Planck Λ CDM universe and covariance matrices estimated with Fisher information matrix techniques. We find that for this setup the Bayes factor provides a substantial evidence in favor of the Λ CDM model over most of the alternatives. We also investigated how well the CPL parametrization approximates various scalar field dark energy models, and identified the location for each dark energy model in the CPL parameter space.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Earth System Model Development - Energy Exascale Earth System Model (2020 Principal Investigator Meeting Report)

As part of the U.S. Department of Energy (DOE) Office of Biological and Environmental Research (BER), the Earth System Model Development (ESMD) program area supports significant research in Earth system model development, including major efforts in the Energy Exascale Earth System Model (E3SM) project. Convened virtually on October 26–29, the 2020 ESMD-E3SM Principal Investigator (PI) Meeting provided a forum to survey ESMD sponsored research, recent progress made by the ESMD science team and the broader Earth system modeling community within and outside of DOE, foster interactions across ESMD projects, and discuss research gaps and opportunities for future advancements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Delayed energy injection model for gamma-ray burst afterglows

The shallow decay phase and flares in the afterglows of gamma-ray bursts (GRBs) are widely believed to be associated with the later activation of the central engine. Some models of energy injection involve a continuous energy flow since the GRB trigger time, such as the magnetic dipole radiation from a magnetar. However, in the scenario involving a black hole accretion system, the energy flow from the fall-back accretion may be delayed for a fall-back time ∼t {sub fb}. Thus, we propose a delayed energy injection model. The delayed energy would cause a notable rise to the Lorentz factor of the external shock, which will 'generate' a bump in the multiple band afterglows. If the delayed time is very short, our model degenerates to the previous models. Our model can explain the significant re-brightening in the optical and infrared light curves of GRB 081029 and GRB 100621A. A considerable fall-back mass is needed to provide the later energy; this indicates that GRBs accompanied with fall-back material may be associated with a low energy supernova so that the fraction of the envelope can survive during eruption. The fall-back time can give meaningful information on the properties of GRB progenitor stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Thermal Energy Storage Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

25 ENERGY STORAGE↗