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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Cubature on Wiener Space: Pathwise Convergence

Cubature on Wiener space (Lyons and Victoir in Proc. R. Soc. Lond. A 460(2041):169-198, 2004) provides a powerful alternative to Monte Carlo simulation for the integration of certain functionals on Wiener space. More specifically, and in the language of mathematical finance, cubature allows for fast computation of European option prices in generic diffusion models.We give a random walk interpretation of cubature and similar (e.g. the Ninomiya-Victoir) weak approximation schemes. By using rough path analysis, we are able to establish weak convergence for general path-dependent option prices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Bertrand and Cournot Mean Field Games

We study how continuous time Bertrand and Cournot competitions, in which firms producing similar goods compete with one another by setting prices or quantities respectively, can be analyzed as continuum dynamic mean field games. Interactions are of mean field type in the sense that the demand faced by a producer is affected by the others through their average price or quantity. Motivated by energy or consumer goods markets, we consider the setting of a dynamic game with uncertain market demand, and under the constraint of finite supplies (or exhaustible resources). The continuum game is characterized by a coupled system of partial differential equations: a backward Hamilton–Jacobi–Bellman partial differential equation (PDE) for the value function, and a forward Kolmogorov PDE for the density of players. Asymptotic approximation enables us to deduce certain qualitative features of the game in the limit of small competition. The equilibrium of the game is further studied using numerical solutions, which become very tractable by considering the tail distribution function instead of the density itself. This also allows us to consider Dirac delta distributions to use the continuum game to mimic finite N-player nonzero-sum differential games, the advantage being having to deal with two coupled PDEs instead of N. We find that, in accordance with the two-player game, a large degree of competitive interaction causes firms to slow down production. The continuum system can therefore be used qualitative as an approximation to even small player dynamic games.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Review of the NURE Assessment of the U.S. Gulf Coast Uranium Province

Historic exploration and development were used to evaluate the reliability of domestic uranium reserves and potential resources estimated by the U.S. Department of Energy national uranium resource evaluation (NURE) program in the U.S. Gulf Coast Uranium Province. NURE estimated 87 million pounds of reserves in the $30/lb U{sub 3}O{sub 8} cost category in the Coast Plain uranium resource region, most in the Gulf Coast Uranium Province. Since NURE, 40 million pounds of reserves have been mined, and 38 million pounds are estimated to remain in place as of 2012, accounting for all but 9 million pounds of U{sub 3}O{sub 8} in the reserve or production categories in the NURE estimate. Considering the complexities and uncertainties of the analysis, this study indicates that the NURE reserve estimates for the province were accurate. An unconditional potential resource of 1.4 billion pounds of U{sub 3}O{sub 8}, 600 million pounds of U{sub 3}O{sub 8} in the forward cost category of $30/lb U{sub 3}O{sub 8} (1980 prices), was estimated in 106 favorable areas by the NURE program in the province. Removing potential resources from the non-productive Houston embayment, and those reserves estimated below historic and current mining depths reduces the unconditional potential resource 33% to about 930 million pounds of U{sub 3}O{sub 8}, and that in the $30/lb cost category 34% to 399 million pounds of U{sub 3}O{sub 8}. Based on production records and reserve estimates tabulated for the region, most of the production since 1980 is likely from the reserves identified by NURE. The potential resource predicted by NURE has not been developed, likely due to a variety of factors related to the low uranium prices that have prevailed since 1980.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Water Footprints of Cassava- and Molasses-Based Ethanol Production in Thailand

The Thai government has been promoting renewable energy as well as stimulating the consumption of its products. Replacing transport fuels with bioethanol will require substantial amounts of water and enhance water competition locally. This study shows that the water footprint (WF) of molasses-based ethanol is less than that of cassava-based ethanol. The WF of molasses-based ethanol is estimated to be in the range of 1,510-1,990 L water/L ethanol, while that of cassava-based ethanol is estimated at 2,300-2,820 L water/L ethanol. Approximately 99% of the water in each of these WFs is used to cultivate crops. Ethanol production requires not only substantial amounts of water but also government interventions because it is not cost competitive. In Thailand, the government has exploited several strategies to lower ethanol prices such as oil tax exemptions for consumers, cost compensation for ethanol producers, and crop price assurances for farmers. For the renewable energy policy to succeed in the long run, the government may want to consider promoting molasses-based ethanol production as well as irrigation system improvements and sugarcane yield-enhancing practices, since molasses-based ethanol is more favorable than cassava-based ethanol in terms of its water consumption, chemical fertilizer use, and production costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

The value of post-extracted algae residue

This paper develops a hedonic pricing model for post-extracted algae residue (PEAR), which can be used for assessing the economic feasibility of an algal production enterprise. Prices and nutritional characteristics of commonly employed livestock feed ingredients are used to estimate the value of PEAR based on its composition. We find that PEAR would have a value lower than that of soybean meal in recent years. The value of PEAR will vary substantially based on its characteristics. PEAR could have generated algal fuel co-product credits that in recent years would have ranged between $0.95 and $2.43 per gallon of fuel produced.

09 BIOMASS FUELS↗
DOE OSTI2019

Spillover as a cause of bias in baseline evaluation methods for demand response programs

Prior research has shown load reduction estimates from residential event-driven demand response programs (e.g., Critical Peak Pricing)using X of the highest Y days with a weather adjustment method are the best performing within the class of currently used baseline methods. However, they are still biased relative to estimates produced from randomized control trials (RCTs), the unbiased “gold standard” evaluation method. In this paper we identify underlying factors that cause some of the bias found in one commonly used baseline method. Rather than simply quantifying bias, our research provides a deeper understanding of what causes the bias and thus can be used to develop more accurate methods that are not subject to these underlying factors. Previous studies have compared various baseline methods relative to each other; however, because all baseline methods are biased, it is impossible to determine the true bias that exists in them. We have access to a unique RCT dataset: the Sacramento Municipal Utility District's study of critical peak pricing. Our analysis of 23 event days over two summers allows us to identify the true bias on load reduction estimates by using the RCT estimates as the unbiased gold standard against which we compare the estimates from the baseline methods. We found that spillover of energy reductions, from hours targeted by a program onto other hours, is one underlying factor that is a major cause of bias in baseline methods. We discuss alternative baseline methods that may not be subject to this same bias.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Exploring the design space of PV-plus-battery system configurations under evolving grid conditions

In this study, we explore how the energy and capacity values of coupled systems comprising solar photovoltaic arrays and battery storage (PV-plus-battery systems) could evolve over time based on the evolution of the bulk power system. Using a price-taker model with simulated hourly energy and capacity prices projected from the present to 2050, we simulate the revenue-maximizing dispatch of a range of DC-coupled PV-plus-battery configurations in three locations in the United States. These configurations are defined by the inverter loading ratio (ILR, the ratio of the PV array capacity to the inverter capacity, which we vary from 1.4 to 2.6) and the battery-inverter ratio (BIR, the ratio of the battery power capacity to the inverter capacity, which we vary from 0.25 to 1.0). Based on each configuration's total value, we estimate the breakeven costs needed to justify each incremental increase in ILR (holding BIR constant) or BIR (holding ILR constant). We find that, in a future with low-cost renewable energy technologies, PV-plus-battery system ILRs can be economically increased to around 2.0-2.4 at a BIR of 1.0, depending on solar resource. Our results indicate that a likely evolution of PV-plus-battery system design will be increasingly greater battery power capacity to mitigate the declining PV capacity value, which will, in turn, enable increasingly higher ILRs to further increase energy value. The extent to which PV-plus-systems will be deployed with increasingly higher ILRs depends primarily on whether PV cost declines outpace declining value and increasing curtailment over time.

14 SOLAR ENERGY↗
DOE OSTI2023

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Cost impact of hexose-to-pentose sugar ratios for biomanufacturing

Central to the long-term vision for biomanufacturing is the ability to deconstruct plant cell walls to sugars that microbes can convert to products. Aside from glucose, the most abundant sugar in biomass is xylose, a pentose sugar. Industrially relevant microbes have been engineered to co-ferment xylose and glucose. Most nth plant technoeconomic analyses (TEAs) assume similar consumption rates and product yields for both sugars, but in reality, xylose is consumed more slowly. Feedstocks can be selected, or engineered, to alter the glucan-to-xylan ratio (GXR) but no TEAs have quantified the impact of this strategy systematically. This study explores the cost impacts of varying the glucan-to-xylan ratio (GXR) from 1.9 to 6.7 for co-fermenting glucose and xylose to ethanol and bisabolene. The minimum selling prices (MSPs) for both products decrease as the GXR increases, with the largest reductions at shorter residence times. For instance, with an increase in GXR from 1.9 to 6.7, ethanol’s MSP drops by 16 %, 5 %, and 3 % at 24, 72, and 144 h, respectively, while bisabolene’s MSP declines by 23 %, 20 %, and 15 % at 24, 72, and 120 h. Particularly for early-stage commercialization, the results suggest that altering or selecting for feedstocks with higher GXR can minimize capital costs by reducing optimal residence times. Capital-constrained biorefineries operating with shorter residence times can justify paying up to 1.5X to 2X the price for feedstocks with a higher GXR, based on the expected improvements in their product yield and overall process economics.

Delayed xylose utilization↗
DOE OSTI2015

Cost-effectiveness Analysis on Measures to Improve China's Coal-fired Industrial Boiler

Tackling coal-burning industrial boiler is becoming one of the key programs to solve the environmental problem in China. Assessing the economics of various options to address coal-fired boiler is essential to identify cost-effective solutions. This paper discusses our work in conducting a cost-effectiveness analysis on various types of improvement measures ranging from energy efficiency retrofits to switch from coal to other fuels in China. Sensitivity analysis was also performed in order to understand the impacts of some economic factors such as discount rate and energy price on the economics of boiler improvement options. The results show that nine out of 14 solutions are cost-effective, and a lower discount rate and higher energy price will result in more energy efficiency measures being cost-effective. Both monetary and non-monetary barriers to energy-efficiency improvement are discussed and policies to tackle these barriers are recommended. Our research aims at providing a methodology to assess cost-effective solutions to boiler problems.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2014

Variations in embodied energy and carbon emission intensities of construction materials

Identification of parameter variation allows us to conduct more detailed life cycle assessment (LCA) of energy and carbon emission material over their lifecycle. Previous research studies have demonstrated that hybrid LCA (HLCA) can generally overcome the problems of incompleteness and accuracy of embodied energy (EE) and carbon (EC) emission assessment. Unfortunately, the current interpretation and quantification procedure has not been extensively and empirically studied in a qualitative manner, especially in hybridising between the process LCA and I-O LCA. To determine this weakness, this study empirically demonstrates the changes in EE and EC intensities caused by variations to key parameters in material production. Using Australia and Malaysia as a case study, the results are compared with previous hybrid models to identify key parameters and issues. The parameters considered in this study are technological changes, energy tariffs, primary energy factors, disaggregation constant, emission factors, and material price fluctuation. It was found that changes in technological efficiency, energy tariffs and material prices caused significant variations in the model. Finally, the comparison of hybrid models revealed that non-energy intensive materials greatly influence the variations due to high indirect energy and carbon emission in upstream boundary of material production, and as such, any decision related to these materials should be considered carefully. - Highlights: • We investigate the EE and EC intensity variation in Australia and Malaysia. • The influences of parameter variations on hybrid LCA model were evaluated. • Key significant contribution to the EE and EC intensity variation were identified. • High indirect EE and EC content caused significant variation in hybrid LCA models. • Non-energy intensive material caused variation between hybrid LCA models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Social impacts of earthquakes caused by gas extraction in the Province of Groningen, The Netherlands

Gas extraction from the Groningen gasfield in the northern Netherlands has led to localised earthquakes which are projected to become more severe. The social impacts experienced by local residents include: damage to property; declining house prices; concerns about the chance of dykes breaking; feelings of anxiety and insecurity; health issues; and anger. These social and emotional impacts are exacerbated by the increasing distrust Groningen people have towards the national government and the gas company, NAM, a partnership between Shell and ExxonMobil. The earthquakes have reopened discussions about the distribution of benefits from gas production and the extent to which benefits are retained locally. Mitigation of the impacts is attempted, but the lack of trust decreases the effectiveness of the mitigation measures. The extent of this experience of previously-unforeseen, unanticipated impacts suggests that a new social and environmental impact assessment needs to be undertaken, and a new Social Impact Management Plan (SIMP) and Impacts and Benefits Agreement (IBA) developed, so that the project can regain its legitimacy and social licence to operate. In addition to conventional gas, this paper has wider relevance for unconventional gas developments, for example shale gas extraction by hydraulic fracturing methods (fracking). - Highlights: • Gas production in Groningen has caused over 1000 earthquakes. • The induced seismicity has caused many social impacts. • Impacts include building damage, reduced house prices, fear and health issues. • Mitigation measures attempted to date are inadequate. • Distrust towards the national government and operator hinders mitigation efforts. • Gas production in Groningen has lost its social licence to operate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A methodology for understanding the impacts of large-scale penetration of micro-combined heat and power

Co-generation at small kW-e scale has been stimulated in recent years by governments and energy regulators as one way to increasing energy efficiency and reducing CO 2 emissions. If a widespread adoption should be realized, their effects from a system's point of view are crucial to understand the contributions of this technology. Based on a methodology that uses long-term capacity planning expansion, this paper explores some of the implications for an electric power system of having a large number of micro-CHPs. Results show that fuel cells-based micro-CHPs have the best and most consistent performance for different residential demands from the customer and system's perspectives. As the penetration increases at important levels, gas-based technologies - particularly combined cycle units - are displaced in capacity and production, which impacts the operation of the electric system during summer peak hours. Other results suggest that the tariff design impacts the economic efficiency of the system and the operation of micro-CHPs under a price-based strategy. Finally, policies aimed at micro-CHPs should consider the suitability of the technology (in size and heat-to-power ratio) to meet individual demands, the operational complexities of a large penetration, and the adequacy of the economic signals to incentivize an efficient and sustainable operation. Highlights: Capacity displacements and daily operation of an electric power system are explored; Benefits depend on energy mix, prices, and micro-CHP technology and control scheme; Benefits are observed mostly in winter when micro-CHP heat and power are fully used; Micro-CHPs mostly displace installed capacity from natural gas combined cycle units; and, Tariff design impacts economic efficiency of the system and operation of micro-CHPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Enhanced deep neural networks with transfer learning for distribution LMP considering load and PV uncertainties

As the flexibility of generation and demand increases in distribution systems, the residential loads are emerging as a promising means to participate in demand response and the transactive energy market. Market pricing is an instrumental mechanism for the distribution system operator to exploit the full potential of the flexible resources. The distribution locational marginal price (DLMP) can be used to guide the residential load consumption. This type of market signal helps the distribution system operator to optimize the scheduling of all resources while satisfying related network constraints through a day-ahead market. However, solving the optimization problem for large-scale systems can be computationally expensive. To address the scalability and practicability limitations of the DLMP framework, a learning-based approach is proposed in this paper to complement the day-ahead distribution market framework. Here, the proposed approach combines long short-term memory and transfer learning to develop deep neural network that can capture the spatial–temporal correlation of the input data. The model can determine the optimal DLMP for each node in a distribution system without the system parameters required to formulate the optimization problem. Testing results on IEEE 33-bus and 123-bus systems show that the proposed approach can generate a comparable DLMP against the optimization solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Correlations and clustering in wholesale electricity markets

We study the structure of locational marginal prices in day-ahead and real-time wholesale electricity markets. In particular, we consider the case of two North American markets and show that the price correlations contain information on the locational structure of the grid. We study various clustering methods and introduce a type of correlation function based on event synchronization for spiky time series, and another based on string correlations of location names provided by the markets. As a result, this allows us to reconstruct aspects of the locational structure of the grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Impacts of increasing penetration of renewable energy on the operation of the power sector

Here in this paper, we consider 38 forward-looking scenarios of the U.S. electricity system and analyze the impacts of increased variable renewable energy on system operation. We find increased demand for flexibility, which is provided by a wide range of technologies. We also observe changes in the timing of the highest and lowest electricity prices, as well as an increase in the number of very low energy price hours.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Highlights: • Combined energy conversion of MSW and agricultural residue biomass is examined. • The model optimizes the financial yield of the investment. • Several system specifications are optimally defined by the optimization model. • The application to a case study in Greece shows positive financial yield. • The investment is mostly sensitive on the interest rate, the investment cost and the heating oil price. - Abstract: Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.

09 BIOMASS FUELS↗