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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Retention of Cr in Meta-kaolin-based geo-polymeric Materials under Oxidation and Carbonation - 17453

Alkali activated alumino-silicates, often referred to as geo-polymers, are considered promising immobilization matrices for contaminants due to their high sorption capacity, durability and low leachability. For some contaminants they may prove superior to cement pastes that are conventional immobilization materials in waste management applications. However, estimating the retention capacity of some contaminants under environmental conditions that include oxidation and carbonation and may induce a valance change, is complicated. These contaminants tend to be soluble under oxidizing condition and form precipitates under reducing conditions. Thus, contaminant retention is highly dependent on the initial oxidation state at which the metal was introduced, as well as the matrix sorption ability, ability to resist oxidation and carbonation, and the contaminant leachability. Moreover, carbonation in considered one of the most important degradation mechanisms in cementitious material, causing porosity reduction and significant changes in contaminant leachability, however, geo-polymers have considerably lower Ca content relative to cements, or none, and the effect of carbonation on these pastes is less clear. Thus, contaminant release mechanisms and rates must be estimated based upon exposure to various atmospheres appropriate to waste management applications. In this study we aim to estimate the sorption capacity, and leachability of Cr from a meta-kaolin based geo-polymer, doped with Cr, as a function of its oxidation state and carbonation. Cr has a high valance range from +6 to 0 similar to Tc, and is used as its simulant in the current study. Sodium dichromate was used as an oxidized source metal material. To induce reducing conditions, ascorbic acid was added except for experimental control cases. The samples were aged under N{sub 2}, 98% N{sub 2} + 2% CO{sub 2}, CO{sub 2} deficient air and air environments under constant relative humidity. Following aging, samples were subject to equilibrium leaching as a function of pH (EPA Method 1313) and monolith mass transport rate testing (EPA Method 1315). Mass balance calculations, based on the results of a pH dependent leaching test, have shown that oxidized Cr samples lost 85-95% of their Cr content, whereas, the reduced Cr samples lost only 20% of their Cr content. On the other hand, the leachability of Si and Al is much higher in the reduced-Cr samples then in the samples with oxidized Cr, and their natural pH is up to 2.5 pH units lower than that of the oxidizing cases. Thus, we conclude that the combination of the reducing agent and the spike chemistry influence the matrix formation. Sample aging have not resulted in any significant change in the Cr-leaching behavior of the oxidizing matrices in the pH dependent leaching test, although a significant decrease in the natural pH, of 1.5 pH unit, was observed upon exposure to elevated CO{sub 2} levels (2%), probably due to the formation of Na-carbonate species. The pH and leaching behavior of the reduced Cr samples under the various aging conditions have not yielded significant variation either in their natural pH or in their leaching behavior. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

Reduction of hexavalent chromium by fasted and fed human gastric fluid. II. Ex vivo gastric reduction modeling

To extend previous models of hexavalent chromium [Cr(VI)] reduction by gastric fluid (GF), ex vivo experiments were conducted to address data gaps and limitations identified with respect to (1) GF dilution in the model; (2) reduction of Cr(VI) in fed human GF samples; (3) the number of Cr(VI) reduction pools present in human GF under fed, fasted, and proton pump inhibitor (PPI)-use conditions; and (4) an appropriate form for the pH-dependence of Cr(VI) reduction rate constants. Rates and capacities of Cr(VI) reduction were characterized in gastric contents from fed and fasted volunteers, and from fasted pre-operative patients treated with PPIs. Reduction capacities were first estimated over a 4-h reduction period. Once reduction capacity was established, a dual-spike approach was used in speciated isotope dilution mass spectrometry analyses to characterize the concentration-dependence of the 2nd order reduction rate constants. These data, when combined with previously collected data, were well described by a three-pool model (pool 1 = fast reaction with low capacity; pool 2 = slow reaction with higher capacity; pool 3 = very slow reaction with higher capacity) using pH-dependent rate constants characterized by a piecewise, log-linear relationship. These data indicate that human gastric samples, like those collected from rats and mice, contain multiple pools of reducing agents, and low concentrations of Cr(VI) (< 0.7 mg/L) are reduced more rapidly than high concentrations. The data and revised modeling results herein provide improved characterization of Cr(VI) gastric reduction kinetics, critical for Cr(VI) pharmacokinetic modeling and human health risk assessment. - Highlights: • SIDMS allows for measurement of Cr(VI) reduction rate in gastric fluid ex vivo • Human gastric fluid has three reducing pools • Cr(VI) in drinking water at < 0.7 mg/L is rapidly reduced in human gastric fluid • Reduction rate is concentration- and pH-dependent • A refined PK model is used to characterize inter-individual variability in Cr(VI) gastric reduction capacity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Hydropower Energy Storage Capacity (HESC) Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogs characteristics that are relevant to evaluating reservoir storage and estimates of energy storage capacity based on varying levels of detail. Hydropower dams and reservoirs were included based on information from the National Inventory of Dams (NID; USACE, 2021) and Global Reservoir and Dam (GRanD v1.3) and Existing Hydropower Assets datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Estimates of energy storage capacity include: • Level 1 – nominal energy storage capacity based on maximum storage capacities and hydraulic head • Level 2 – nominal energy storage capacity based on historical models or observations of reservoir volume and hydraulic head. These estimates are provided based on capacity from the entire historical period as well as monthly values. • Level 3 – modeled energy generation based on volume-elevation relationships, historical storage, observed/modeled inflows, and hydraulic capacity of turbines and calculated both as overall and on a monthly basis. • Level 4 – modeled energy generation incorporating information from Level 3 and operational constraints. For facilities where installed capacity is known, there are also estimates for discharge duration (the length of time when a facility could provide generation at a given capacity).

13 HYDRO ENERGY↗
DOE OSTI2015

Pd doped reduced graphene oxide for hydrogen storage

Pd nanoparticles dispersed reduced graphene oxide sample has been prepared by a simple chemical method using hydrazine as the reducing agent. Based on XRD and {sup 13}C MAS NMR studies it is confirmed that, Pd nanoparticles are effectively mixed with the reduced graphene oxide sample. Maximum hydrogen storage capacity has been estimated to be ∼1.36 wt % at 123K. Improved hydrogen storage capacity of Pd incorporated sample can be explained based on the phenomenon of spillover of atomic hydrogen.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Akutan Geothermal: Resource Report

Geothermal energy resources are present in the Hot Springs Bay Valley geothermal area, and the City has invested considerable money and time in the exploration of the resource for future use. Exploration activities funded primarily through a grant the City was awarded from Alaska Energy Authority and later supplemented by the U. S. Department of Energy (DOE), with cost share from the City. The exploration led to the development of a geothermal resource conceptual model that was built and refined between 2008 and 2018. During this period, geological and geophysical studies, exploration drilling and other activities were completed, including a preliminary feasibility study for a power project, investigations of the terrain for suitability for access and development, environmental and archeological review, plus TG well abandonment and a review of economic considerations. The model of the resource predicts that there is a viable geothermal resource in two general areas: on the northwest edge of Hot Springs Bay Valley going northwest of the valley (hot springs area) and southwest of the Valley (fumarole area). The resource temperature for the valley area is expected to be about 170°C (340°F) and given the size and permeability estimates (with a factor for the level of confidence in the estimates), the mean power capacity of the outflow resource is 3 MWe and the P50 (most likely) power capacity is 1 MWe. The fumarole area has an expected resource temperature of 240°C (464°F) and given the size and permeability estimates mean capacity is 20 MWe and the P50 (most likely) capacity is 9 MWe. Permeability is the most difficult factor to predict and has a significant impact on the available geothermal fluids and therefore the amount of power that can be generated. The uncertainty in this value is the main reason for lower confidence in the likelihood of exploration success and the wide range in predicted MW values. The permeability has been difficult to locate as indicated by the results of the flow test at AK-3 in 2017. The test resulted in the production of some fluid, but due to low permeability, the recharge to the wellbore was too slow to sustain flow. The greatest probability of overall MWe production is in the fumarole region, but development is hampered by poor accessibility. The extremely high cost of road building for exploratory drilling, put an end to planning at an intermediate stage of the project and refocused attention on the viability of development in the hot spring outflow part of the resource. The City will be determining what the next steps are with AK-3, which is still that is still open and maintained in a suspended status in HSBV. While AK-3 remains accessible (not plugged with cement) it will need to be maintained. The City has a bond with AOGCC that will remain in place until the well is abandoned. GRG recommends that the well be maintained open as an asset for the foreseeable future.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Predicting Field Efficiency of Round-Baling Operations in High-Yielding Biomass Crops

Model simulations for bioenergy harvest planning need to utilize equipment-capacity relationships for equipment operating under the high-yield conditions typical of a biomass crop. These performance assumptions have a direct bearing on the estimates of machine capacity, the number of machines required, and, therefore, the cost to fulfill the biorefinery plant demands for a given harvest window. Typically, two major issues in these models have been poorly understood: the available time required to complete the harvest operation (often called probability of workdays) and the capacity of the harvest equipment as impacted by yield. Simulations use annual yield estimates, which incorporate weather events, to demonstrate year-to-year effects. Some simulations also incorporate potential yield increases from genetically modified energy crops. There are limited field performance data for most current forage equipment used for harvesting high-yield biomass crops. Analysis shows that the impact of wrap/eject time for round balers resulted in a 50% reduction in achieved throughput capacity (Mg/h). After the maximum throughput is reached, the cost of the round bale operation (3.23 USD/Mg) is double that of the large-square baler (1.63 USD/Mg). The round baler achieved throughput capacity is 50% less (32.7 Mg/h compared to 71.0 Mg/h) than the large-square baler.

09 BIOMASS FUELS↗
DOE OSTI2022

Forecasting battery capacity and power degradation with multi-task learning

Lithium-ion batteries degrade due to usage and exposure to environmental conditions, which affects their capability to store energy and supply power. Accurately predicting the capacity and power fade of lithium-ion battery cells is challenging due to intrinsic manufacturing variances and coupled nonlinear ageing mechanisms. In this paper, we propose a data-driven prognostics framework to predict both capacity and power fade simultaneously with multi-task learning. The model is able to predict the degradation trajectory of both capacity and internal resistance together with knee-points and end-of-life points accurately at early-life stage. The validation shows an average percentage error of 2.37% and 1.24% for the prediction of capacity fade and resistance rise, respectively. The model's ability to accurately predict the degradation, facing capacity and resistance estimation errors, further demonstrates the model's robustness and generalizability. Compared with single-task learning models for forecasting capacity and power degradation, the model shows a significant prediction accuracy improvement and computational cost reduction. This work presents the highlights of multi-task learning in the degradation prognostics for lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2018

Western Sector Injection Well Performance Testing

A total of eight short duration injection tests were conducted on wells at the M-Area Western Sector In-Situ Chemical Oxidation (ISCO) test site. For each injection event, approximately 200 gallons of water were gravity drained into the well casing. Pressure response was monitored in the injection well and these data were used to estimate the injection capacity of each well. Nearby injection wells were used as observation wells and data from these wells were used to estimate local hydraulic conductivity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Evaluation of Rooftop Solar Potential in Chernihiv and Lviv, Ukraine, and Efficacy of High-Resolution 3D Data Digital Twins [Slides]

NREL evaluated rooftop solar photovoltaic (PV) siting opportunities in the cities of Chernihiv and Lviv, Ukraine, leveraging very-high-resolution 3D elevation data to calculate technical potential. The study assessed total rooftop solar capacity and annual energy production. In Chernihiv and Lviv, 116,503 buildings were analyzed for their rooftop solar potential. The buildings in the study areas include a mixture of residential, commercial, and industrial buildings, characterized by diverse roof shapes and sizes. The total estimated rooftop solar capacity is 332 MWDC in Chernihiv and 873 MWDC in Lviv with annual energy production up to 376.2 GWhDC in Chernihiv and 995.5 GWhDC in Lviv. This accounting provides a clear estimate of the potential rooftop solar installations that could be realized under optimal conditions, considering both technical constraints and the geographic distribution of available rooftop space. Related to Russia's invasion of Ukraine, NREL estimates loss from buildings damaged or destroyed of 2,754 buildings, 20.15 MWDC of capacity, and 22,869 MWhDC of annual energy production in Chernihiv as well as a loss of 1,316 buildings, 34.49 MWDC of capacity, and 39,369 MWhDC of annual energy production in Lviv. The study also assessed the feasibility of adapting this methodology on a national scale using either simulated digital surface models (DSMs) or a digital twin approach. While the very-high-resolution DSM provided more precise results, the simulated DSM demonstrated reasonable accuracy for broader applications in modeling aggregated distributed solar supply. The feasibility of using a digital twin for Ukraine's national rooftop solar potential is considered promising, with certain limitations in areas with highly variable building stock and heavy war damage.

14 SOLAR ENERGY↗
DOE OSTI2018

The geospatial and economic viability of CO 2 storage in hydrocarbon depleted fractured shale formations

Hydrocarbon depleted fractured shale (HDFS) formations could be attractive for geologic carbon dioxide (CO 2 ) storage. Shale formations may be able to leverage existing infrastructure, have larger capacities, and be more secure than saline aquifers. We compared regional storage capacities and integrated CO 2 capture, transport, and storage systems that use HDFS with those that use saline aquifers in a region of the United States with extensive shale development that overlies prospective saline aquifers. We estimated HDFS storage capacities with a production-based method and costs by adapting methods developed for saline aquifers and found that HDFS formations in this region might be able to store with less cost an estimated ~14× more CO 2 on average than saline aquifers at the same location. The potential for smaller Areas of Review and less investment in infrastructure accounted for up to 84% of the difference in estimated storage costs. We implemented an engineering-economic geospatial optimization model to determine and compare the viability of storage capacity for these two storage resources. Across the state-specific and regional scenarios we investigated, our results for this region suggest that integrated CCS systems using HDFS could be more centralized, require less pipelines, prioritize different routes for trunklines, and be 6.4–6.8% ($5-10/tCO 2 ) cheaper than systems using saline aquifers. In conclusion, overall, CO 2 storage in HDFS could be technically and economically attractive and may lower barriers to large scale CO 2 storage if they can be permitted.

42 ENGINEERING↗
DOE OSTI2020

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. This report includes the geologic interpretations and storage resource estimates (SREs) for three potential storage reservoirs calculated using six methodologies.

geologic characterization↗
DOE OSTI2024

Impacts of Climate Change on the Generation Potential of Solar and Wind Energy Systems in India

Low-carbon energy sources like wind and solar are essential for decarbonizing the electricity sector. In addition, the cost of electricity generated from these sources has plummeted over the last decade. Therefore, these energy sources are poised to take a significant share of the total installed capacity soon. However, they are susceptible to the impacts of climate change as their generation potential depends on the weather conditions. Estimating the installed capacity requirements of solar and wind energy to decarbonize the power sector without accounting for these possible changes in generation potential could lead to missing out on the set climate goals and meeting future electricity demand. This study evaluates the effect of climate change on the generation potential of wind and solar energy systems in India for two future periods, 2050 and 2070, under two climate scenarios or Shared Socioeconomic Pathway (SSP): SSP245 and SSP585. Almost all regions show a decrease, and most regions show a significant decline (>5%) in the generation potential of solar Photovoltaic (PV) as compared to 2010 levels under both climate scenarios and future periods. The changes in the generation potential of wind energy are more significant (>10%), and the majority of regions show a decline in generation potential. Southwestern and central regions show an increase in wind generation potential for 2070 as compared to 2050 levels under the SSP245 scenario and the SSP585 scenario, respectively.

climate change↗
DOE OSTI2017

8760-Based Method for Representing Variable Generation Capacity Value in Capacity Expansion Models: Preprint

Capacity expansion models (CEMs) are widely used to evaluate the least-cost portfolio of electricity generators, transmission, and storage needed to reliably serve demand over the evolution of many years or decades. Various CEM formulations are used to evaluate systems ranging in scale from states or utility service territories to national or multi-national systems. CEMs can be computationally complex, and to achieve acceptable solve times, key parameters are often estimated using simplified methods. In this paper, we focus on two of these key parameters associated with the integration of variable generation (VG) resources: capacity value and curtailment. We first discuss common modeling simplifications used in CEMs to estimate capacity value and curtailment, many of which are based on a representative subset of hours that can miss important tail events or which require assumptions about the load and resource distributions that may not match actual distributions. We then present an alternate approach that captures key elements of chronological operation over all hours of the year without the computationally intensive economic dispatch optimization typically employed within more detailed operational models. The updated methodology characterizes the (1) contribution of VG to system capacity during high load and net load hours, (2) the curtailment level of VG, and (3) the potential reductions in curtailments enabled through deployment of storage and more flexible operation of select thermal generators. We apply this alternate methodology to an existing CEM, the Regional Energy Deployment System (ReEDS). Results demonstrate that this alternate approach provides more accurate estimates of capacity value and curtailments by explicitly capturing system interactions across all hours of the year. This approach could be applied more broadly to CEMs at many different scales where hourly resource and load data is available, greatly improving the representation of challenges associate with integration of variable generation resources.

14 SOLAR ENERGY↗
DOE OSTI2024

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Heat capacity of Mg 3 Sb 2 , Mg 3 Bi 2 , and their alloys at high temperature

The thermoelectric figure of merit reported for n-type Mg 3 (Sb,Bi) 2 compounds has made these materials of great engineering significance, increasing the need for accurate evaluations of their thermal conductivity. Thermal conductivity is typically derived from measurements of thermal diffusivity and determination of the specific heat capacity. The uncertainty in this method (often 10% or more) is frequently attributed to measurement of heat capacity such that estimated values are often more accurate. Inconsistencies between reported thermal conductivity of Mg 3 (Sb,Bi) 2 compounds may be attributed to the different values of heat capacity measured or used to calculate thermal conductivity. The high anharmonicity of these materials can lead to significant deviations at high temperatures from the Dulong-Petit heat capacity, which is often a reasonable substitute for measurements at high temperatures. Herein, a physics-based model is used to assess the magnitude of the heat capacity over the entire temperature range up to 800 K. The model agrees in magnitude with experimental low-temperature values and reproduces the linear slope observed in high-temperature data. Owing to the large scatter in experimental values of high-temperature heat capacity, the model is likely more accurate (within ±3%) than a measurement of a new sample even for doped or alloyed materials. It is found that heat capacity for the solid solution series can be simply described (for temperatures: 200K≤T≤800K ) by the polynomial equation: c p [Jg –1 K –1 ]=3NR/M W (1 + 1.3 × 10 –4 T – 4 × 10 3 T –2 ), where 3 NR = 124.71 J mol –1 K –1 , M W is the molecular weight [gmol –1 ] of the formula unit being considered, and T is temperature in K . This heat capacity is recommended to be a standard value for reporting and comparing the thermal conductivity of Mg 3 (Sb,Bi) 2 including doped or alloyed derivatives. Furthermore, a general form of the equation is given which can be used for other material systems

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Review of Behind-the-Meter Solar Generation Modeling and Forecasting

Solar photovoltaic systems largely integrated within the distribution grid are operated 'behind-the-meter' and power generation cannot be directly monitored by most utilities. The increasing penetration of behind-the-meter solar photovoltaic systems can deter efficient network and market operations due to variability and uncertainty in net load, which is exacerbated by limited visibility and the difficulty in analyzing the hosting capacity. Risk introduced by behind-the-meter solar contributions may hinder reliable and secure grid operations due to biased system monitoring and forecasts. Accurate behind-the-meter estimations, together with capacity and specification forecasts, thus play a key role in balancing supply and demand and this article reviews the pertinent literature, identifying key characteristics and predictive methods for efficient behind-the-meter solar photovoltaic generation. Forecasting is central to methods herein. The fundamental characteristics of behind-the-meter solar forecasting, including which methods are applicable for scenario-driven use cases, are driven by the metrics most useful for system-wide performance evaluation. To this aim, the literature is reviewed with a focus on forecasting applications for aggregate, regional behind-the-meter generation useful to bulk system and utility operations. As distinguished from net load forecasting, subtleties in these coincident tasks are explored before concluding with recommendations for current practice and future implementations.

behind-the-meter↗
DOE OSTI2025

Floating Photovoltaic Technical Potential: A Novel Geospatial Approach on Federally Controlled Reservoirs in the United States

Floating photovoltaic generation is a rapidly expanding sector of the solar energy industry, and understanding the quantity that can feasibly be installed is a crucial step to understand its role in future energy systems. This paper presents a novel spatially explicit methology of FPV potential for federally owned and managed reservoirs in the United States that uses site-specific attributes of reservoirs to estimate available area and potential generation capacity. The analysis finds that the proportion reservoir area that is found to be available for FPV development is similar to assumed values used in previous research on average, however there is a wide variability in this proportion on a site by site basis. Potential FPV generation capacity on these reservoirs is estimated to be in the range of 861 to 1,042 GWdc depending on input assumptions, likely representing a significant portion of future US solar generation needs. This work represents an advancement in methods used to estimate FPV potential that presents many natural extensions for further research.

floating solar↗