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519 records · Page 29

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY↗

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗

Characterization of solid particle candidates for application in thermal energy storage and concentrating solar power systems

Thermal energy storage (TES) enables concentrating solar power to remain competitive in the renewable energy mix by firming up intermittent solar resource and providing grid services such as load shifting. Free from siting constraints, stand-alone TES systems show promise as a low-cost alternative to traditional pumped-storage hydropower or compressed air energy storage. At the core of all TES technologies is a storage medium, the selection of which governs many aspects of system design and operation. Although the majority of commercial installations utilize molten salts, solid particles can demonstrate stability over wider temperature ranges. This amounts to increased energy storage densities and corresponding reductions in system cost which is essential in achieving low-cost energy storage. In this work, eight solid particle candidates are systematically identified and screened for application in a specific particle-TES system. The five most promising candidates (CARBO CP and HSP, calcined flint clay (CFC), brown fused alumina (BFA), and silica sand) are further characterized by size and morphology for fluidization suitability, flowability for particle transport, and thermal stability. Calcined flint clay and brown fused alumina are eventually down-selected due to thermal instability at the target operational temperature of 1200 °C. Although the physical characteristics of CARBO outperform silica sand in all categories examined, the marginal performance gains are considered insufficient to justify the additional media cost so silica sand is selected as the leading candidate. Within the silica sand (α-quartz) space, the high end of Geldart Group B particles is identified to satisfy the target fluidization regime for the application of interest without compromising particle flowability. Here, in focused testing, Silica 460 is shown to exhibit sufficient stability through long-duration (500-hour) thermal and cyclic testing (1200 °C), 10-hour testing at 1400 °C, and in contact with candidate refractory containment materials. Finally, an average heat capacity of 1.1 J/g∙ °C is measured over 300-1200 °C with a quartz inversion enthalpy (ΔH α-β ) of 10.7J/g.

14 SOLAR ENERGY↗

High-Temperature Active Magnetic Bearing Development for Supercritical CO 2 Machinery Applications

Hermetic machinery utilizing gas bearings for MW-scale supercritical CO 2 (sCO 2 ) machinery applications can have significantly lower power loss and enable improved cycle efficiency compared to conventional machinery with oil-lubricated bearings. Active magnetic bearings (AMBs) are another option anticipated to have similar power loss and load capacity to gas bearings as well as offering larger mechanical tolerances, the ability to tune properties, and high reliability due to lack of mechanical wear. AMBs also have proven commercial experience at MW-scale, though environments for high-temperature sCO 2 power cycle machinery conditions are novel. Besides the potential impact of AMBs for sCO 2 turbomachinery, the technology also offers promising benefits for steam and gas turbines for power generation, compressors and expanders for industrial heat and power, and in other oil and gas and space applications. The goals of this project were to conceptual design an AMB and perform material testing. Conceptual designs for radial and thrust AMBs were produced based on a hermetically-sealed sCO 2 machinery waste-heat recovery (WHR) application for sizing and loads, and choosing a target design temperature of 540°C useful for high-temperature sCO 2 turbines for concentrating solar power (CSP) applications. Conceptual designs were initially developed for multiple radial and thrust AMBs with spreadsheet-based calculations before selecting one of each to develop further using higher-fidelity design methods for magnetic and structural performance. It was found that the radial AMB at 540°C was feasible, but the thrust AMB needed to be limited to 315°C for high-speed operation. The decision for a reduced-temperature thrust AMB was the result of several significant conclusions: 1) Hiperco 50A, originally chosen for good magnetic performance at high temperature, had insufficient strength for high-speed operation, so it was replaced with 17-4 PH. 2) The reduced magnetic performance from 17-4 PH yielded a larger bearing size, reducing the strength margin. 3) This ultimately led to a creative design implementing a more-compact E-core topology, compared to the original (conventional) C-core, and an integral shaft-disk with Hirth joint connection. These conceptual designs are unique for the size and temperature in CO 2 , relevant for MW-scale CSP applications. Long term, high temperature test data was generated for several materials, filling a void in the current body of literature. Corrosion and magnetic performance measurements were produced for PM materials (Alnico 5-7C, Alnico 9C, and SmCo) with and without nickel-coating for environments of high-temperature CO 2 up to 550°C at atmospheric pressure and 450°C at 103 bar for up to 6,000 hours. Corrosion measurements were also produced for Hiperco 50, a SM material relevant for AMB laminations, with and without C5 coating. Comparisons were also made for 450°C and 550°C, atmospheric pressure air exposures up to 5,000 hours. Results generally show that coatings can be effective at improving oxidation resistance of the bare materials, and Alnicos generally outperformed SmCo after high-temperature exposure. In addition to technical feasibility demonstrated by the design, economic feasibility was demonstrated by updating the TEA from the reference machine, re-evaluating it with CAPEX and OPEX to reflect estimated changes from process-lubricated bearings to AMBs. AMBs were shown to be comparable in performance to process-lubricated bearings, still showing a notable improvement over conventional machinery architecture with oil-lubricated bearings.

42 ENGINEERING↗

Dissolution of Fluoride Salts in Hanford Tank Waste

The Direct Feed High-Level Waste (DFHLW) strategy seeks to bypass the Hanford Waste Treatment and Immobilization Plant Pretreatment Facility while retaining some processing functions to maximize waste feed loading and minimize high-level waste (HLW) waste volume. The DFHLW flowsheet needs leaching, washing, and solids concentration operations either in new or existing tanks. The effectiveness and efficiency of sludge washing has a substantial impact on DST space, mission duration, and the evaporation and low-activity waste (LAW) treatment operations required by these large wash-water additions. One target species requiring washing is fluoride. The HLW glass composition limits for fluorine drive operations to dissolve fluoride-bearing salts into the LAW fraction and thereby maximize waste loading in HLW glass. The fluoride in many high-level wastes at Hanford is predominantly in the form of fluoride-salt precipitates: villiaumite (NaF), kogarkoite (Na 3 FSO 4 ), and natrophosphate (Na 7 F(PO 4 ) 2 ·19H 2 O). Fluoride produces melter off-gas that creates corrosion risk in the off-gas system piping, while the sulfate and phosphate in the fluoride double salts kogarkoite and natrophosphate can be detrimental to glass waste loading. Fluoride salts are sparingly soluble, with solubilities ranging from approximately 40 to 130 kg per kL of pure water, and the dissolution kinetics of the three fluoride salts are not well known. Unexpected delays in a tank dissolution process could be encountered as a result of the lack of information about dissolution rates. In addition, if the double salts show transient non-stoichiometric dissolution of fluoride versus phosphate or sulfate, unexpectedly high concentrations of one of these other constituents could be produced. Washington River Protection Solutions authorized Pacific Northwest National Laboratory to collect the available data for fluoride salt dissolution rate, provide a scoping estimate of dissolution time if possible, and identify gaps in the understanding and predictive capability for estimating dissolution time. Open literature and Hanford reports were reviewed to document, understand, and (where possible) evaluate limitations on fluoride salt equilibria and dissolution kinetics, including both mass transport and surface reaction rate. Scoping estimates of dissolution time were made for mass-transfer-controlled dissolution of spherical particles of fluoride salts suspended in liquid. This is not the only potential governing mechanism; dissolution could be substantially slower if the surface reaction rate (the rate of release of ions from the surface) is the controlling mechanism. When the minimum amount of water for complete dissolution is used and the slip velocity between the liquid and suspended particles is less than or equal to the terminal settling velocity, the estimated mass-transfer rates allow 0.1 mm particles of fluoride salt to dissolve in minutes at 25 °C in water containing no other dissolved salts. Much larger solids, such as the 6-mm chunks that have been seen in heels, could take a few hours to more than a week to dissolve. The actual dissolution times will depend strongly on the actual slip velocity, the extent of particle suspension, constraint by surface reaction rates, the ratio of solvent to solid, and the presence of common ions that shift the solubility equilibria to restrict dissolution of fluoride salts.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Ion Exchange Processing of AW-105 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) Program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AW-105 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the small-scale ion exchange testing with 9.2 L of diluted and filtered supernate from Tank 241-AW-105 (hereafter referred to as AW-105) at 16 °C (62 °F). One of the waste acceptance criteria (WAC) for the Waste Treatment Plant (WTP) Low-Activity Waste Facility is that the waste must contain less than 3.18×10 -5 Ci 137 Cs per mole of Na. For the AW-105 tank waste to meet this criterion, only 0.225% of the influent 137 Cs concentration may be delivered to the WTP; this requires a Cs decontamination factor of 445. Testing with AW-105 matched current Tank Side Cesium Removal (TSCR) facility prototypic operations where a lead-lag configuration was used until the lag column reached the WAC limit, then a polish column was brought online for continued processing in a lead-lag-polish column configuration. Feed was processed at 1.9 bed volumes (BVs) per hour; the flowrate, in terms of contact time with the crystalline silicotitanate (CST) bed, matched the expected flowrate at TSCR. The Cs-decontaminated product was retained for vitrification testing (to be reported separately). The lead column reached 83% Cs breakthrough after processing ~1500 BVs of feed; the 50% Cs breakthrough was interpolated from the breakthrough data and occurred at 1041 BVs. Despite the AW-105 having a significantly higher K concentration (0.55 M compared to 0.10 M), testing compared to previous AP-107 ion exchange column testing at 16 °C showed no difference in BVs processed to reach the WAC on the lead column and only an approximate ~20 BV decrease in volume processed to reach the WAC limit on the lag column. The negligible differences in capacity despite the 5x concentration differences in K was determined to be due to the significantly lower NO3 concentration in the AW-105 supernate compared to the AP-107 tank waste matrix. A comparison in breakthrough curves for the two tests also indicated slightly faster kinetic behavior in the AW-105, with the variations in feed matrices (lower NO3 concentration) likely responsible for the deviation. The Cs effluent from the lag column reached the WAC limit after processing 772 BVs. Anticipating this breakthrough point, the polish column was preemptively installed around 675 BVs. Cs breakthrough from the lag column began at 300 BVs, reaching 1.10×10 1 µCi/mL, or 14.13 % Cs breakthrough, after processing all 1500 BVs of feed. The polish column processed nominally 830 BVs and reached 2.10×10 -1 µCi/mL, or 0.27 % Cs breakthrough at the conclusion of the test. Table S.1 and Figure S.1 summarize the observed column performance and relevant Cs loading characteristics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High-resolution hourly surrogate modeling framework for physics-based large-scale building stock modeling

Surrogate modeling can play a key role in reducing high computational burdens for large-scale physics-based modeling and uncertainty quantification. With the rapid development of large-scale building stock energy modeling, surrogate modeling has also begun to be widely applied in this field; however, most existing surrogate models lack hourly time resolution for regional-scale modeling, which is essential for understanding building demand profiles and grid impacts. Further, there is generally a lack of necessary data and feature engineering frameworks specific to building modeling for efficiently managing large datasets and complex computations. Furthermore, this paper proposes a modeling framework for large-scale (city-/region-scale), high-resolution, high-fidelity surrogate building stock energy models. Our developed framework consists of six modules: (1) building stock energy modeling (ComStock TM and ResStock TM ), (2) data engineering for large simulation data, (3) high performance computing workflow, (4) feature engineering, (5) machine learning model development, and (6) model performance evaluation. Two case studies apply the developed framework in both residential and commercial building stock analysis to demonstrate its computational efficiency and surrogate modeling accuracies. Results show that surrogate models, when efficiently trained using the HPC workflow module, reach a high level of modeling accuracy for two case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Repurposing Fossil-Fueled Assets For Energy Storage

The annual retirement of U.S. coal-fired electricity generation units (CF-EGU) is at an all-time high and is expected to continue. This loss of reliable baseload generation, combined with predicted growth of variable renewable energy (VRE) generation, is expected to stress grid reliability as the number of load-following resources drops below the experienced load variability. Many regions are already experiencing challenges, and fossil retirement-related warnings by the North American Electric Reliability Corp. are becoming more dire. All CF-EGU retirements pose significant challenges to asset owners, local workforces, and their communities. Repurposing a retiring CF-EGU as a long-duration energy storage plant can address these challenges and offer a suite of additional benefits to asset owners, the grid, and society. This project performed a techno-economic evaluation and assessment of repurposing a Duke Energy fossil-fueled asset (in particular, a coal plant) into an energy storage system by integrating the retiring asset with a Malta long duration Pumped Heat Energy Storage (PHES) system. The project validated the technoeconomic benefits of repurposing retiring coal plants into long-duration energy storage using Malta’s PHES. Key findings for this project are summarized below: (1) Technical: (a) Retiring coal plants (and other steam turbine fossil generation) can be repurposed to enable the clean energy transition using Malta’s technology. (b) For older retiring coal plants, repurposing the site and electrical interconnection for a standalone PHES plant is the most economically favorable option. (c) For newer coal plants where there is also a local peaking capacity need, repowering the steam cycle into a hybrid integration with PHES is attractive. (d) A process was developed to assist fossil generation owners in choosing the best path for each plant’s circumstances. (2) Economic (a) Communities facing economic challenges caused by the retirement of fossil generation would benefit from repurposing the plant as long-duration energy storage using Malta’s PHES. (b) On a $/MW basis, repowering retiring coal units into Malta PHES plants can maintain the same number and types of jobs and economic activity. (c) For a 70% carbon reduction scenario, a 10-hour Malta PHES plant is more economic for the asset owner than similar-power 4-hour batteries. This project showed that repurposing a retiring coal unit into thermal energy storage, by integrating it with a Malta PHES system, makes techno-economic sense. At least two integration options are available, with the optimal solution depending on the coal plant and its location. Repurposing retiring coal plant into energy storage results in economic benefits for the plant owner and local communities.

20 FOSSIL-FUELED POWER PLANTS↗

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗

Evaluation of thermostat location for multizone commercial building performance

In multi-zone buildings, it is often found that a single shared thermostat controls more than one conditioned zones. Although these shared zones are supposed to have similar thermal needs (e.g., cooling and heating load), in reality, they are not mainly due to different orientations, sizes of windows, occupancy, space types, etc. This can cause unnecessary energy waste or thermal discomfort for the occupants. How to quantify this impact in multizone buildings remains a research gap. Therefore, this study aims to evaluate the impact of different sensor (i.e., thermostat) locations for multizone commercial buildings through a comprehensive modeling study. Here, two different scenarios for the sensor locations were selected to evaluate the impact in terms of energy and thermal comfort. The scenario (1) is that one to five sensors distributed among the five zones, but the sensor readings from selected zones will be used for no-sensor zones, which is no-mean sensor scenario. The scenario (2) is that one to five sensors distributed among the five zones, but the average temperature from the shared zones will be used for each of the shared zones, which is a mean sensor scenario. The uncertainty analysis was performed for different sensor location scenarios.(a)The major findings from an energy perspective, for scenario (1), the differences of cooling energy go as high as 17% more or 12% less, compared with the baseline. For heating energy consumption, the discrepancies go as high as 51% more or 52% less, compared with baseline. For site energy consumption, the discrepancies go as high as 3.2% more or 3.2% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.2% more or as low as 1.0% less, compared with baseline. For scenario (2), the discrepancies of cooling energy go as high as 3% more, or 0.5% less, compared with the baseline. For heating energy consumption, the discrepancies, are go as high as 10.1% more or as low as 3.0% less, compared with baseline. For site energy consumption, the discrepancies go as high as 1.3% more or 0.3% less, compared with baseline. For fan energy consumption, the discrepancies go as high as 3.1% more or as low as 1.0% less, compared with baseline.(b) In terms of the indoor thermal comfort, for the no-mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 1,200 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 740 h, compared with the baseline. For the mean-sensor scenarios, the discrepancies of unmet hours for cooling mode can be as high as 750 h, compared with the baseline. The discrepancies of unmet hours for heating mode can be as high as 50 h, compared with the baseline.

42 ENGINEERING↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

Direct Air Capture of CO 2 and Delivery to Photobioreactors for Algal Biofuel Production (Final Report)

A mobile DAC system was designed and constructed to pair with photobioreactors growing algae for biofuel production. The DAC system was designed as a versatile research system, rather than a compact production unit. The system was constructed and mounted on a mobile skid to facilitate transportation to the algae production site. Within the DAC system, CO 2 was captured using amine-loaded monoliths that allow for high CO 2 uptake with low pressure drop. The CO 2 is collected using a Global Thermostat patented temperature/vacuum swing adsorption (TVSA) process. Amine sorbents and process conditions were optimized to produce 10 to >20 g CO 2 .h-1. The stability of the amine sorbents was also studied, with sorbent modifications made to improve stability to degradation by oxidation. An Algenol-developed Spirulina strain (Arthrospira platensis AB2293) was selected as the production cyanobacterial strain. AB2293 cultured was inoculum for outdoor production following PBR installation by Algenol. The PBR system was composed of three independent PBRs, with each PBR composed of four hanging bags internally recirculated by a liquid turnover pump. The PBRs were operated outdoors in Atlanta, GA, and integrated with the DAC system. Algae were grown with similar productivity using DAC-CO 2 as algae grown using pure CO 2 obtained commercially (Airgas). Throughout the experimental duration, no discoloration was observed, and cellular morphology was consistent between the two experimental treatments. An LCA including lifecycle greenhouse gas emissions, full life cycle inventory of the Algenol system and the DAC system and integrated DAC+PBR system was developed. Lifecycle greenhouse gas emissions were calculated for capture of carbon dioxide using input from Global Thermostat and the National Renewable Energy Laboratory. Three scenarios for energy provision were evaluated: a natural gas combined heat and power system sized to meet the electricity requirement, a natural gas combined heat and power system sized to meet the process heat requirements, and a system without on-site power that procures the electricity from the grid. In all three cases, as expected, the major contributor to the emissions is the energy consumption associated with the desorption step of the DAC process. The LCA quantified the reduced potential energy and greenhouse gas emissions of heat and mass integration of DAC and Algenol compared to unintegrated DAC and Algenol systems. A life cycle assessment of the role of sorbent productivity and lifetime was also developed. The development of more robust, oxidation resistant DAC sorbents may enable small reductions in energy requirements and in lifecycle greenhouse gas emissions and other environmental impacts. NREL performed techno-economic analysis (TEA) to identify the integration scenario most likely to achieve a 15% cost reduction target versus the baseline. Heat and mass integration of DAC and the PBR is critical to minimizing the MFSP. The baseline case utilizes no heat and mass integration, and the DAC system provides 100% of the CO 2 required by the photobioreactors (20 tonnes/hr), operating for 12 hours/day capturing 40 tonnes CO 2 /operating hour. The minimum fuel selling price (MFSP) of ethanol calculated from the baseline case was $10.68/gal ethanol. This corresponds with a targeted MFSP of $9.07/gal ethanol (or 15% reduction). This target was achieved by integration Option 2a with the greatest cost reduction of 17.8% (or $8.78/gal) and integration Option 2b with a cost reduction of 16.4% (or $8.93/gal). Reductions in MFSP are attributed to two primary process considerations: (a) CO 2 storage at night reduces the capital expenses associated with DAC (i.e., increasing on-stream time); and (b) distributed DAC scenarios (DAC-PBR integration Options 2a and 2b) make use of boiler and DAC CHP flue gas CO 2 (free). Direct air capture on-stream time was one of the largest contributors to MFSP reduction.

09 BIOMASS FUELS↗

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

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Improvement of Coal Power Plant Dry Cooling Technology through Application of Cold Thermal Energy Storage

The U.S. power infrastructure is currently heavily reliant on water cooling. The power plants in the U.S. account for approximately 40% of freshwater withdrawals, with 90% of it used in condenser cooling. The most used cooling technology in coal-fired power plants is a once-through condenser; however, this cooling method requires high water withdrawal rates and results in thermal pollution of the water source. Wet WCTs offer an alternative to once-through condensers due to much lower water withdrawals. However, these systems suffer from water consumption through evaporation making them undesirable options in areas subject to droughts and in arid areas. The direct dry cooled condensers (ACCs) and dry cooling towers (DCT) account for 1.8%, hybrid cooling (ACC + WCT) accounts for 0.5%, while other cooling technologies represent the rest (0.7%). The ACC/DCTs represent an attractive alternative for power plants; however, this technology has not been widely adopted in the US (less than 2% of power plants) due to its negative impact on plant performance. As a rule of thumb, dry cooling results in performance penalty equivalent to approximately 2%-point efficiency loss compared to wet cooling, although the actual magnitude varies with ambient dry bulb temperature, DBT which may vary considerably during the day. As DBT increases, the plant power output decreases, reaching a minimum at the hottest period of the day, which usually coincides with the highest electricity demand for air condition load. Therefore, performance of power plants using DCT/ACC cooling technology is the lowest during the summer mid-day when ambient temperature is the highest. For example, the decrease of the inlet air temperature to the DCT/ACC by 2 Deg C could generate up to 5% additional power at peak demand. It is, therefore, important to improve dry cooling technology to maintain the viability of coal-fired power plants in a carbon constrained future. The method for reducing the cooling air temperature and keeping it constant would mitigate this problem significantly. Objectives of this project were to develop, design, evaluate, and demonstrate a cost-effective system for improving performance of a DCT or ACC for thermal (coal-fired) power plant applications using a low-cost heat storage materials, such as pervious concrete (PC) and phase change material (PCM). Thus, the study focused on development of the system(s) that could be used to alleviate the difficulties in operating DCT/ACC during the summer months by storing cold energy during the nighttime in inexpensive materials PC and PCM and using it during the hottest period(s) of the day. Since very large quantities of cold energy need to be stored to make an impact on performance of a large power plant, it is essential that the storage materials and associated cold energy storage design(s) are inexpensive and the system is simple to build, maintain and operate. To achieve the project objectives, a comprehensive approach, including material development and characterization, component and system modeling, and laboratory- and prototype-scale experiments, was employed including modeling of the system components and of the entire system, development (engineering) of the materials for the heat storage modules of the Cold Thermal Energy Storage System (CTESS) and determination of their properties, design, manufacturing and setup of the laboratory- and prototype-scale test facility and testing, design, manufacturing and setup of the prototype-scale test facility. A modular design of CTESS was employed, where representative modules were designed as the integrated direct contact heat exchanger and thermal energy storage (TES) system. CTESS modules were manufactured and tested. Two prototype-scale designs of the CTESS modules were developed and tested. The use of CTESS increases plant generation increases since it lowers air temperature entering ACC/DCT and keeps it constant during the hottest time of the day. For a PCM-based CTESS, the ambient air temperature is lowered close to the PCM phase change temperature. The duration of the cooling effect depends on the latent heat and mass of PCM in the CTESS. For this project, commercial grade CaCl2 hexahydrate (CaCl2·6H2O or CC6) PCM with phase change temperature of 25 Deg. C was used due to its low cost. For practical reasons, the CTESS was designed to maintain the cooling effect for four hours. The low phase change temperature associated with the commercial grade PCM used in CTESS results in considerably higher improvement in net generation compared to the laboratory (pure) grade. The resistance to heat transfer results in lower net generation compared to the ideal case where resistance to heat transfer is zero. The results demonstrate that CTESS is effective in improving the performance of a dry cooling system. However, its effectiveness depends on the relationship between the ambient air conditions and PCM phase change temperature. As is the case with the heat rejection system, for the best performance, the PCM used in CTESS would need to be matched to the ambient air conditions. The results obtained in this report for selected geographical locations are valid for CC6 and demonstrate that the level of performance to be achieved by the technology will be location-dependent, as is the case with the air cooled condensers. The methodology for engineering of PC-PCM-based heat storage medium is applicable to other PCMs that may need to be used for other ambient air conditions and geographical locations.

01 COAL, LIGNITE, AND PEAT↗

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗