Search NASA⌕ Search

SEARCH · Search NASA

Results for “Energy - Storage”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Modeling Savings for ENERGY STAR Smart Home Energy Management Systems

The objective of this study was to develop a repeatable and defensible methodology to analyze the energy savings for Home Energy Management Systems (HEMS) that meets the minimum requirements for certification under ENERGY STAR ® Smart Home Energy Management System (SHEMS) Version 1. Mandatory connected loads include a smart thermostat, two smart lights, and one smart power strip or smart outlet. Control strategies must include feedback to occupants through an in-home display, user programming, occupancy sensor-based controls, and responsiveness to utility signals such as demand response programs. Several occupant behavior patterns were selected to quantify the range of energy savings potential for a HEMS with this basic functionality. A literature review was conducted to establish realistic room-by-room occupancy levels and usage patterns for connected devices. A series of event-driven hourly profiles were created, followed by adjustments based on application of HEMS control strategies to thermostats, interior lighting, and plug load schedules. EnergyPlus modeling was performed using these hourly schedules in three locations (Boston, Houston, and Phoenix) to examine climate dependence of energy savings. Total site energy savings ranged from 4.3 to 27.1 MBtu/year (7%-35%), and utility bill savings ranged from $\$$123 to $\$$670/year (6%-29%). The highest predicted savings was realized by occupants that were not energy conscious prior to HEMS installation, but highly engaged with the HEMS controls once the system was installed. The smart thermostat accounted for most of the savings, followed by the smart power strip. Smart lighting did not save a significant amount of energy in our analysis, based on an assumption that efficient LEDs with no standby power would normally be installed anyway.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Development of a Sizing and Modeling Platform for District Energy Systems with Geothermal Heat Pumps

Existing tools for community or urban scale energy system modeling and simulation are often limited in their capabilities and require expert-level modeling proficiency to develop system models. To fill this gap, this paper proposes an integrated sizing and modeling platform for district energy systems with geothermal heat pumps. The proposed platform takes in geometric and non-geometric user inputs related to the buildings, borefield, and district energy loop. Then, the platform sizes the geothermal heat exchanger, generates a corresponding district energy system model, and runs an annual simulation automatically. We validated the simulation performance of the borefield in our tool against EnergyPlus. A case study is provided in this paper to demonstrate the workflow and simulation result plausibility of the proposed platform.

decarbonization↗
DOE OSTI2025

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗
DOE OSTI2021

Nonequilibrium kinetic freeze-out properties in relativistic heavy ion collisions from energies employed at the RHIC beam energy scan to those available at the LHC

In this paper, we investigate the kinetic freeze-out properties in relativistic heavy ion collisions at different collision energies. We present a study of standard Boltzmann-Gibbs blast-wave (BGBW) fits and Tsallis blast-wave (TBW) fits performed on the transverse momentum spectra of identified hadrons produced in Au + Au collisions at collision energies of $\sqrt{s_{\rm{NN}}}=$7.7 –200 GeV at the Relativistic Heavy Ion Collider (RHIC), and in Pb + Pb collisions at collision energies of $\sqrt{s_{\rm{NN}}}=$ 2.76 and 5.02 TeV at the Large Hadron Collider (LHC). The behavior of strange and multistrange particles is also investigated. We found that the TBW model describes data better than the BGBW one overall, and the contrast is more prominent as the collision energy increases as the degree of nonequilibrium of the produced system is found to increase. From TBW fits, the kinetic freeze-out temperature at the same centrality shows a weak dependence of collision energy between 7.7 and 39 GeV, while it decreases as collision energy continues to increase up to 5.02 TeV. The radial flow is found to be consistent with zero in peripheral collisions at RHIC energies but sizable at LHC energies and central collisions at all RHIC energies. We also observed that the strange hadrons, with higher temperature and similar radial flow, approach equilibrium more quickly from peripheral to central collisions than light hadrons. The dependence of temperature and flow velocity on nonequilibrium parameter (q - 1) is characterized by two second-order polynomials. Both a and dξ from the polynomials fit, related to the influence of the system bulk viscosity, increase toward lower RHIC energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Terrestrial radiative cooling: Using the cold universe as a renewable and sustainable energy source

Photonic materials designed at wavelength scales have enabled a range of emerging energy technologies, from solid-state lighting to efficient photovoltaics that have transformed global energy landscapes. Daytime passive radiative cooling materials shed heat from the ground to the cold universe by taking advantage of the terrestrial thermal radiation that is as large as the renewable solar energy. Newly developed photonic materials permit subambient cooling under direct sunshine, and their applications are expanding rapidly enabled by scalable manufacturing. We review here the recent advancement of daytime subambient radiative cooling materials, which allow energy-efficient cooling and are paving the way toward technologies that harvest the coldness from the universe as a new renewable energy source.

Science & Technology - Other Topics↗
DOE OSTI2020

Development of a High-Energy Neutron Sniffer and Subsequent Dose Quantification for High-Energy Particle Accelerator Shielding Surveys

The objective of this research is to design a portable neutron detector that is lightweight and responds to neutrons with energies of 20 MeV and greater. The instrument will be used as a ‘sniffer’ probe for identifying shielding weaknesses at high-energy particle accelerators and be paired with a plastic scintillator to quantify the high-energy neutron dose equivalent. The sniffer probes are two different sizes and comprised of either cesium iodide or sodium iodide, all doped with thallium, making a total of four detectors. The probes were calibrated to respond only to radiations with 8 MeV electron equivalent energy or higher, vastly reducing detector response from background and lower energy radiations. The sniffer probes were tested using californium- 252 and americium-beryllium sources, followed by high-energy (up to 800 MeV) neutron exposures at the Los Alamos Neutron Science Center Weapons Neutron Research (WNR) facility. The sniffer probes were then used to identify areas around the accelerator facility where elevated levels of high-energy radiation was present and the plastic scintillators were placed in these locations to determine the high-energy neutron dose equivalent. The dose equivalent is calculated by measuring the 12 C(n,2n) 11 C reaction, which has a 20.4 MeV neutron threshold. Two locations behind the WNR facility were identified with the probes and the dose equivalent rates from neutron energies above 20 MeV were calculated to be 1.24 mrem/h behind flightpath 30-left and 1.53 behind flightpath 30-right. Of the four sniffer probes, the 2-inch x 2-inch cesium iodide is the recommended probe for performing high-energy shielding surveys. The larger crystal size yields higher sensitivity at lower count rates and the more dense material increases the likelihood of interaction within the crystal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Tsdat: An Open-Source Data Standardization Framework for Marine Energy and Beyond

Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same domain, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications, which rely on large quantities of data from multiple sources. To address these challenges, the open-source Time-Series Data Pipelines (Tsdat) Python framework was developed by Pacific Northwest National Laboratory, with strategic guidance and direction provided by the National Renewable Energy Laboratory and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the marine energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat framework and the data standards within which it operates. A beta version of Tsdat has been released and is being used by several projects in marine energy, wind energy, and building energy systems.

big data↗
DOE OSTI2024

Energy-dependent and Energy-integrated Two-moment General-relativistic Neutrino Transport Simulations of a Hypermassive Neutron Star

Abstract We compare two-moment-based energy-dependent and three variants of energy-integrated neutrino transport general-relativistic magnetohydrodynamics simulations of a hypermassive neutron star. To study the impacts due to the choice of the neutrino transport schemes, we perform simulations with the same setups and input neutrino microphysics. We show that the main differences between energy-dependent and energy-integrated neutrino transport are found in the disk and ejecta properties, as well as in the neutrino signals. The properties of the disk surrounding the neutron star and the ejecta in energy-dependent transport are very different from the ones obtained using energy-integrated schemes. Specifically, in the energy-dependent case, the disk is more neutron-rich at early times and becomes geometrically thicker at later times. In addition, the ejecta is more massive and, on average, more neutron-rich in the energy-dependent simulations. Moreover, the average neutrino energies and luminosities are about 30% higher. Energy-dependent neutrino transport is necessary if one wants to better model the neutrino signals and matter outflows from neutron star merger remnants via numerical simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands

There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5% and 0.5% for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4% and 7.0% for the detailed medium office building model and high-rise building model, respectively. Here this study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Who will be making wave energy? A community-driven design approach toward just and sustainable energy futures in Alaska

Renewable energy transition, once thought of as a singular, large-scale switch in industrial energy generating technologies from fossil fuels to renewables, have gained a broader set of requirements, including the need for justice and environmental protection. While discourse around policy and process has grown to consider these requirements, the focus of design of new renewable energy projects and technologies remains dominantly fixed on maximizing energy production, and renewables are falling short of meeting the requirements of just energy transitions. Meanwhile, in design studies, participatory and co-design approaches which explicitly consider justice in both process and outcomes have long been theorized and applied. However, applications of these approaches to renewable energy project design are under-theorized. In this paper, we explore the effectiveness of the adoption and adaptation of a co-design approach called Community-Driven Design (CDD) in enabling meaningful participation prior to technological maturity and bringing the attention of designers to a more diverse set of energy futures focused on justice and sustainability. Here, we do so by developing and testing the approach with community members in Sitka, AK, USA. We conclude that the approach has the potential to increase meaningful participation. Furthermore, we conclude that through diverse understandings of energy and the emergence of design narratives that engage with the complexity of vulnerability, accountability, and resilience, CDD led designers to consider justice, sustainability, and a diverse set of possible energy futures both within and beyond Sitka.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Our Renewable Energy Future: The Remarkable Story of How Renewable Energy Will Become the Basis for Our Lives

Our Renewable Energy Future delves into the clean energy technology evolution and where our energy system is going. While the book's foundation is technology innovation, it brings a unique perspective that technology alone is not what has brought about the explosive growth of renewable energy and offers fresh insights into how technology, economics, social dynamics, policy, and geopolitics are forces affecting our energy future. This book is a culmination of Dr Arent's lifelong passion for energy, sustainable development, and renewable energy technology. It covers the journey of evolving technology, economics, political economy and geopolitics of clean energy over the last 40 years and provides insights for the coming decades. From a technology perspective, the book traces the arc of recent innovations and synthesizes innovations across multiple interacting perspectives into a description of Our Renewable Energy Future.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Solar Pathways in Federal Energy Assistance Programs: Expanding the Low-Income Home Energy Assistance Program (LIHEAP) and the Weatherization Assistance Program (WAP)

The U.S. Department of Health and Human Services Low-Income Home Energy Assistance Program (LIHEAP) and U.S. Department of Energy Weatherization Assistance Program (WAP) are federal programs to help low-income households reduce their energy costs. LIHEAP provides direct assistance to help households cover energy costs and stay connected to utility services, as well as weatherization and minor energy-related repairs, and WAP provides no-cost energy efficiency measures to reduce energy use and energy bills while also improving home comfort for income-qualified households. Across the U.S., states are implementing or considering solar energy as an eligible measure for LIHEAP and/or WAP funding, but the successful implementation pathways remain largely undocumented. This report fills that gap by analyzing states' LIHEAP and WAP annual plans, surveying administrators from LIHEAP grant recipients and WAP grantees about their challenges implementing solar or barriers to doing so, and conducting interviews and workshops with program administrators.

14 SOLAR ENERGY↗
DOE OSTI2026

Energy Baseline Assessment and Project Considerations for the Wai'anae Moku Community Energy Plan

This report was prepared as a supplement to the Waianae moku community's energy plan and includes results of two activities conducted by the National Laboratory of the Rockies in support of the planning process: (1) an energy baseline assessment and (2) considerations and resources for possible energy projects prioritized by the community in its energy plan. Results of the energy assessment describe the energy landscape in the state of Hawaii, on the island of Oahu, and in the Waianae moku at the time the plan was developed, with the intention of supporting informed community participation in the planning process. Considerations and resources align with each of the energy project ideas identified in the community's energy plan, and are intended to describe the current context and activities related to each, along with possible next steps toward implementation, and additional resources. The report concludes with takeaways for the community to consider as they pursue their energy goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Hybrid Energy System Workflow for Energy Portfolio Optimization

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Highly Resolved Reference Projections of Building Energy Use for the Contiguous United States: Building Sector Energy Baselines, Projection Methods, and Results

This report describes one methodology of projecting energy consumption of the US residential and commercial building sectors using NREL's ResStock™ and ComStock™ as well as growth rates derived from EIA's Annual Energy Outlook (AEO). The impetus for this work is to provide an intermediate method for compiling demand-side sectoral energy projections that is suitable for grid-scale analysis, such as NREL's Standard Scenarios. ResStock and ComStock are physics-based and statistically representative building stock models of the US residential and commercial sector, respectively. Using the 2012 actual meteorological year (AMY) weather data, the sectoral energy baselines are simulated and then segmented along key dimensions (e.g., geography, dwelling/building type). The segmented results are then scaled using the corresponding annual growth rates derived from the 2021 AEO reference case to produce energy projections out to 2050. The compiled result is a demand-side grid model (dsgrid) data set suitable for use in NREL's large-scale grid models, such as the Regional Energy Deployment System (ReEDS). This simple projection method does not endogenously represent how the building stock could evolve through time. Most notably, it does not reflect large-scale electrification, for example, the conversion of space heating, water heating, clothes drying, and cooking from primary fossil fuels to electricity, as this is not part of AEO's reference case assumptions. Nonetheless this approach is more resolved and potentially extensible compared to the current method used by Standard Scenarios's reference case, which augments a sector's total load based on a single growth rate from AEO.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗