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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.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The impact of behavioral and geographic heterogeneity on residential-sector carbon abatement costs

Analyses of monetary and emissions savings from residential efficiency upgrades usually neglect behavioral differences between consumers. Variations in behavior are frequently large: 13% of the U.S. population sets thermostats for cooling at 20 °C (68 °F) or lower and 15% at 25.5 °C (78 °F) or higher. Efficiency analyses should account for behavioral heterogeneity as well as variations in climate and housing characteristics. We model energy and economic savings of efficiency upgrades for U.S. single-family detached houses, accounting for differences in thermostat settings, climate zone, fuel prices, and home characteristics. We consider five efficiency interventions: wall insulation, attic insulation, air sealing, high-efficiency furnaces, and high-efficiency air conditioners. Energy and economic savings vary widely by consumer; the average net present value for wall insulation is $3,020 United States Dollar (USD), but considering heterogeneity, it has a 10th percentile value of -$231 and 90th percentile value of $5,000. Neglecting heterogeneity, technology upgrades can be prioritized from lower to higher carbon abatement costs: air conditioners, wall insulation, furnace, air sealing, and attic insulation. Accounting for heterogeneity reorders this prioritization, and consumer-specific conditions affect mitigation costs such that technologies are mixed in with one another and are no longer arranged one after another. These results indicate that interventions to improve efficiency should consider differences between consumers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Climate impacts on hydropower and consequences for global electricity supply investment needs

Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore the possible consequences of these impacts for the electricity supply sector. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model with downscaled, bias-corrected climate realizations derived from sixteen general circulation models. Consequent impacts on power sector composition and associated emissions and investment costs are explored using the Global Change Assessment Model (GCAM). Changes in hydropower generation resulting from climate change can shift power demands onto and away from carbon intensive technologies, resulting in significant impacts on power sector CO2 emissions for certain world regions—primarily those located in Latin America, as well as Canada and parts of Europe. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity—meaning impacts on power sector investment costs are similar for high and low emissions scenarios. Individual countries where impacts on investment costs imply significant risks or opportunities are identified.

Turner, Sean W. D. (ORCID:0000000344009800)↗
DOE OSTI2019

The retailed gasoline price in China: Time-series analysis and future trend projection

This study introduces a method to systematically project retailed gasoline prices in China and provides projection results. Based on oil taxation and pricing mechanisms in China, this study establishes the statistical relationship between the retailed gasoline prices in China and international crude oil prices using error correction models (ECM), time-series models. Detailed comparison among asymmetric ECM, threshold ECM, and threshold asymmetric ECM are provided. By adopting the ECMs, the study projects the retailed gasoline prices from 2019 to 2050 based on the international crude oil prices from the Annual Energy Outlook provided by the U.S. Energy Information Administration. The results show that the asymmetric responsiveness and the threshold effect exist under current Chinese oil pricing policy with a lag of one month or even shorter in gasoline price adjustment. Moreover, the analysis informs one that, in the short-run, the retailed gasoline prices in China are more sensitive to international crude oil price increases; while in the long-run, the retailed gasoline prices are more sensitive to international crude oil price decreases. Compared with the national average gasoline price in China of 6.04 CNY/Liter in 2017, the national average gasoline price in China is projected to be about 7.64 CNY/Liter (2017 dollar) by 2050.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings

Data-driven building fault detection and diagnostics (FDD) is heavily dependent on sensors. However, common sensors from Building Automation Systems are not optimized to maximize accuracy in FDD. Installing additional sensors that provide more detailed building system information is key to maximizing the performance of FDD solutions. Here in this paper, we present a sensor cost analysis workflow to quantify the economic implications of installing new sensors for FDD using the concept of sensor threshold marginal cost (STMC). STMC does not represent actual sensor cost. Rather, it represents a target cost based on the economic benefit that would be realized through improved FDD performance and one or more specified economic criteria. We calculate STMCs for multiple possible fault types and use fault prevalence information to aggregate STMCs into a single dollar value to determine the cost-effectiveness of a potential sensor investment. We conducted a case study using Oak Ridge National Laboratory's Flexible Research Platform (FRP) test facility as a reference. The case study demonstrates the feasibility of the analysis and highlights the key cost considerations in sensor selection for FDD. The results also indicate that identifying and installing the few key sensor(s) is critical to cost-effectively improve FDD performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Is disaggregation the holy grail of energy efficiency? The case of electricity

This paper aims to address two timely energy problems. First, significant low-cost energy reductions can be made in the residential and commercial sectors, but these savings have not been achievable to date. Second, billions of dollars are being spent to install smart meters, yet the energy saving and financial benefits of this infrastructure - without careful consideration of the human element - will not reach its full potential. We believe that we can address these problems by strategically marrying them, using disaggregation. Disaggregation refers to a set of statistical approaches for extracting end-use and/or appliance level data from an aggregate, or whole-building, energy signal. In this paper, we explain how appliance level data affords numerous benefits, and why using the algorithms in conjunction with smart meters is the most cost-effective and scalable solution for getting this data. We review disaggregation algorithms and their requirements, and evaluate the extent to which smart meters can meet those requirements. Research, technology, and policy recommendations are also outlined. (C) 2012 Elsevier Ltd. All rights reserved.

Armel, KC↗
DOE OSTI2015

Long term energy and emission implications of a global shift to electricity-based public rail transportation system

With high reliance on light-duty vehicles in the present, the future of global transportation system is also geared towards private modes, which has significant energy and emission implications. Public transportation has been argued as an alternative strategy for meeting the rising transportation demands of the growing world, especially the poor, in a sustainable and energy efficient way. The present study analyzes an important yet under-researched question – what are the long-term energy and emission implications of an electric rail based passenger transportation system for meeting both long and short distance passenter transportation needs? We analyze a suite of electric rail share scenarios with and without climate policy. In the reference scenario, the transportation system will evolve towards dominance of fossil based light-duty vehicles. We find that an electric rail policy is more successful than an economy wide climate policy in reducing transport sector energy demand and emissions. Economy wide emissions however can only be reduced through a broader climate policy, the cost of which can be reduced by hundreds of billions of dollars across the century when implemented in combination with the transport sector focused electric rail policy. Moreover, higher share of electric rail enhances energy security for oil importing nations and reduces vehicular congestion and road infrastructure requirement as well.

Chaturvedi, Vaibhav↗
DOE OSTI2015

U.S. oil dependence 2014: Is energy independence in sight?

The importance of reducing U.S. oil dependence may have changed in light of developments in the world oil market over the past two decades. Since 2005, increased domestic production and decreased oil use have cut U.S. import dependence in half. The direct costs of oil dependence to the U.S. economy are estimated under four U.S. Energy Information Administration Scenarios to 2040. The key premises of the analysis are that the primary oil market failure is the use of market power by OPEC and that U.S. economic vulnerability is a result of the quantity of oil consumed, the lack of readily available, economical substitutes and the quantity of oil imported. Monte Carlo simulations of future oil market conditions indicate that the costs of U.S. oil dependence are likely to increase in constant dollars but decrease relative to U.S. gross domestic product unless oil resources are larger than estimated by the U.S. Energy Information Administration. In conclusion, reducing oil dependence therefore remains a valuable goal for U.S. energy policy and an important co-benefit of mitigating greenhouse gas emissions.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2019

Evaluating project level investment trends for the U.S. ESCO industry: 1990–2017

Energy efficiency is widely recognized as a cost-effective strategy to meet energy demand. The U.S. energy service company (ESCO) industry generates significant energy savings and other benefits through installing and maintaining energy efficiency, renewable and other types of projects. In this study, we evaluate factors that may explain trends in the economic performance of U.S. ESCO projects by analyzing project level data for ~7000 U.S. ESCO industry projects. We find that real project investment levels normalized for floor area have increased over time in ESCO projects across market segments. However, the dollar value of energy savings and other reported benefits have not kept pace with increases in real project investment levels over time. The latter have increased 100%–500% in various market segments from 1990 to 2017. We conduct an econometric analysis to decompose the drivers of these underlying trends. Number of measures and a changing mix of conservation measures are the primary factors that correlate with the long-term increase in project investment levels. However, our analysis is only able to account for less than 50% of the increase in real investment levels. Finally, we discuss additional factors, and conclude discussing policy implications and outlining long-term research needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Two trillion gallons: Fuel savings from fuel economy improvements to US light-duty vehicles, 1975–2018

Since 1975, the fuel economy of new light-duty vehicles sold in the U.S. has almost doubled. Fuel economy improvements on laboratory tests gradually became real improvements on the road as newer, more efficient vehicles replaced older less efficient ones. Fleet-wide fuel economy gains produced large fuel savings. In this paper, we show that fuel economy gains measured on laboratory test cycles, adjusted for on-road conditions and weighted by the distribution of vehicles by age and their relative use, closely match estimates by the Federal Highway Administration based primarily on traffic counts and motor fuel tax records. Furthermore, adjusting for the rebound effect of fuel economy on vehicle miles traveled, we estimate the fuel savings, CO 2 emissions reductions and dollars saved on fuel due to fuel economy improvements over the past 43 years. Through the end of 2018, estimated cumulative fuel savings amount to approximately 2 trillion gallons of gasoline. We estimate that roughly one-fifth of the savings can be attributed to gasoline price increases over the period and four-fifths to fuel economy and greenhouse gas (ghg) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Optimizing fluvial flood mitigation strategies: A multi-objective approach for cost-effective and socially-aware infrastructure feasibility analysis

Effective levee planning must balance capital cost, risk reduction, and community priorities. These objectives are rarely optimized together. This study presents a feasibility phase, simulationin-the-loop framework that couples terrain-based flood modeling with a socially aware multiobjective optimizer. Flood risk is measured as Expected Annual Exposed Population (EAEP), obtained by integrating exposure over Annual Exceedance Probability (AEP) nodes, mirroring the Hydrologic Engineering Center's Flood Damage Reduction Analysis (HEC-FDA) expected-annual formulation but with people rather than dollars. Exposure per scenario is computed by overlaying binary inundation masks with a population surface at the tract level. Distributional fairness is encoded through a Group Benefit Share (GBS) constraint that requires high-SVI tracts to receive at least a baseline share of annualized benefits. Capital cost is represented by a height-dependent unit-cost model suitable for screening. This study addresses the two-objective problem, minimize cost and expected annual exposure subject to the GBS constraint, using Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and leveraging Pareto front for feasibility phase decision making. Implemented with terrain-based flood modeling, GeoFlood, for rapid scenario evaluation, the framework is demonstrated in Southeast Texas. The results reveal clear trade-offs among cost, risk, and social benefits and identify non-dominated levee height configurations that satisfy the benefit-share floor. The contributions are a scalable decision support method that operationalizes expected annual population-based risk, embeds enforceable benefit-sharing guarantees, and uses lightweight simulation to explore large design spaces before higher fidelity design stages.

Flood mitigation↗
DOE OSTI2013

Sensitivity of injection costs to input petrophysical parameters in numerical geologic carbon sequestration models

Numerical simulations are widely used in feasibility studies for geologic carbon sequestration. Accurate estimates of petrophysical parameters are needed as inputs for these simulations. However, relatively few experimental values are available for CO2-brine systems. Hence, a sensitivity analysis was performed using the STOMP numerical code for supercritical CO2 injected into a model confined deep saline aquifer. The intrinsic permeability, porosity, pore compressibility, and capillary pressure-saturation/relative permeability parameters (residual liquid saturation, residual gas saturation, and van Genuchten alpha and m values) were varied independently. Their influence on CO2 injection rates and costs were determined and the parameters were ranked based on normalized coefficients of variation. The simulations resulted in differences of up to tens of millions of dollars over the life of the project (i.e., the time taken to inject 10.8 million metric tons of CO2). The two most influential parameters were the intrinsic permeability and the van Genuchten m value. Two other parameters, the residual gas saturation and the residual liquid saturation, ranked above the porosity. These results highlight the need for accurate estimates of capillary pressure-saturation/relative permeability parameters for geologic carbon sequestration simulations in addition to measurements of porosity and intrinsic permeability.

Cost estimate↗
DOE OSTI2021

A comprehensive techno-eco-assessment of CO 2 enhanced oil recovery projects using a machine-learning assisted workflow

Carbon dioxide enhanced oil recovery (CO 2 -EOR) projects not only extract residual oil but also sequestrate CO 2 in the depleted reservoirs. Here, this study develops a machine-learning-based workflow to co-optimize the hydrocarbon recovery, CO 2 sequestration volume and project net present value (NPV) simultaneously. Considering the trade-off relationships among the objective functions, support vector regression with Gaussian kernel (Gaussian- SVR) proxies are coupled with multi-objective particle swarm optimization (PSO) protocol and generate Pareto optimal solutions. Taking advantage of the high computational efficacy of the proxy model, economic uncertainties introduced by tax credits, capital costs and oil price are investigated by this study. The results indicate that the tax incentive policy (Section 45Q) plays a vital role in enhancing the economic returns of CO 2 -EOR projects, especially under the depression of crude oil market. The proposed workflow has been successfully implemented to optimize a water alternative CO 2 (CO 2 -WAG) injection project in a depleted oil sand in the US. The optimization results yield an incremental oil production of 15.8 MM STB and 1.37 MM metric tons of CO 2 storage in a 20-year development strategy, with the highest project NPV to be 205.6 MM US dollars.

03 NATURAL GAS↗
DOE OSTI2023

Cost analysis of hydrogen production by high-temperature solid oxide electrolysis

In this study, we estimate construction and operation costs of gigawatt-scale solid oxide electrolysis (SOE) facilities for producing high purity hydrogen gas from water. Manufacturing and assembly costs for two types of SOE cell stacks are estimated using a detailed design for manufacture and assembly (DFMA®) analysis. Modular balance of plant (BOP) process equipment is designed and sized with Aspen®, and cost estimated using equipment vendor quotes. Factory and on-site assembly and installation costs for SOEC stack and BOP equipment integration into modular SOE process units are calculated using a simplified DFMA® method. Total stack costs on a stack input power (SIP) basis reduce to <$100/kW e DC SIP for >500 MW e DC SIP /year production rates with electrode cermet, interconnects, and high-temperature heat treatments dominating the total cost. Integration of stacks with larger BOP equipment operating at higher pressures offers ~36% cost reduction in total facility capital cost due to an economies of physical scale effect since BOP equipment comprises >50% of facility costs. Optimized H 2 prices decrease from ~$\$$4/kgH 2 to ~$\$$2/kgH 2 for 1 GWe DCSIP facilities using $\$$0.025/kWh electricity price. All costs are reported in 2021 US dollars.

08 HYDROGEN↗
DOE OSTI2025

Cost analysis of alternative large-scale high-temperature solid oxide electrolysis hydrogen production facilities

We extend our past cost analysis of gigawatt-scale solid oxide electrolysis (SOE) facilities that produce high purity hydrogen gas from water by estimating construction and operating costs for three new alternative design cases: (1) offsite feed steam generation; (2) near-atmospheric pressure (NAP) stack; and (3) onsite electric boiler feed steam generation. Pressure effects on hydrogen electrode-(cathode-)supported SOE cell (SOEC) stack performance are estimated for the same assumed cell and stack construction and used to determine facility-wide stack capital costs for achieving a fixed H2 production at different pressures. Modular balance of plant (BOP) process equipment capital costs are estimated for each new alternative design case using our past equipment sizing, design, and cost data and scaling relationships. Furthermore, we update BOP equipment sizing and design for the NAP case using Aspen®. Vendor quotes for electric boilers are used to estimate costs for the electric boiler design case. Factory and onsite assembly and installation costs for SOEC stacks and BOP equipment are calculated using our past simplified first-principles approach. First-of-a-kind (FOAK) and N th -of-a-kind (NOAK) production maturity cost estimates are included for all results. The case with NAP stacks offers the lowest facility total capital cost (TCC, ~23% lower than base) while use of small electric boilers requires the highest TCC (~3% higher than base). H 2 production prices decrease from the base of ~$\$2.17$ /kgH 2 to ~$\$1.92$/kgH 2 for 1 GW e DC SIP facilities utilizing NAP stacks supplied by offsites steam situated in large modules and blocks for $\$0.030$/kWh e and $0.009/kWh t prices for electricity and thermal energy, respectively. We report all costs in 2021 US dollars.

Balance of plant (BOP) process equipment↗
DOE OSTI2025

Ultra-high efficiency hydrogen production using a large-scale solid oxide electrolysis cell system

Efficient and cost-effective production of clean hydrogen is key to decarbonizing the production of hard-to-abate industries, such as chemicals, fuels, steel, cement and many other commodities that form the basis of modern societies. High-temperature steam electrolysis (HTSE) has recently become commercially available and offers opportunities for producing hydrogen at higher efficiency and lower cost than competing low temperature technologies. In this work, we report world record setting hydrogen production efficiency from large-scale prototype HTSE systems based on solid oxide electrolysis cell (SOEC) technology. Independent tests performed at Idaho National Laboratory (INL) employed a Bloom Energy 100 kW SOEC system to achieve a hydrogen production direct current specific electric energy consumption as low as 36.7 kWh per kilogram of hydrogen. Remarkably, similar high efficiencies in the range of 36–39 kW/kg-H2 were obtained over a wide range of hydrogen production rates and even during dynamic ramping as the hydrogen production and electric power consumption of the system were varied between 20 % and 100 % of nominal conditions. Furthermore, these test results validate previous projections that commercial SOEC systems can produce clean hydrogen at efficiencies approaching 100 % for less than 2 U S. dollars per kilogram when located near sources of inexpensive, low-grade heat and clean electricity.

08 HYDROGEN↗