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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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EV Shuttle Bus Pilot

The EV Shuttle Bus Pilot dataset contains data and analysis from Hocking-Athens-Perry Community Action's demonstration of an electric bus on routes of their rural Athens Public Transit system. The vehicle used in the demonstration was a Ford E-450 cutaway equipped with an electric drivetrain, a 127-kWh battery system by Motiv Power Systems, and a cabin upfit by Turtle Top. Data gathered include route assignments, running time and distance, fuel economy, and charge cycles. A comparison of the vehicle's observed duty cycle with duty cycle modeling from other rural transit fleets in the National Transit Database is included to help better understand the rural adoption potential for this fleet technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Spatial-Temporal Synchrophasor Data Characterization and Analytics in Smart Grid Fault Detection, Identification, and Impact Causal Analysis

An approach of big data characterization for smart grids (SGs) and its applications in fault detection, identification, and causal impact analysis is proposed in this paper, which aims to provide substantial data volume reduction while keeping comprehensive information from synchrophasor measurements in spatial and temporal domains. Especially, based on secondary voltage control (SVC) and local SG observation algorithm, a two-layer dynamic optimal synchrophasor measurement devices selection algorithm (OSMDSA) is proposed to determine SVC zones, their corresponding pilot buses, and the optimal synchrophasor measurement devices. Combining the two-layer dynamic OSMDSA and matching pursuit decomposition, the synchrophasor data is completely characterized in the spatial-temporal domain. To demonstrate the effectiveness of the proposed characterization approach, SG situational awareness is investigated based on hidden Markov model based fault detection and identification using the spatial-temporal characteristics generated from the reduced data. To identify the major impact buses, the weighted Granger causality for SGs is proposed to investigate the causal relationship of buses during system disturbance. The IEEE 39-bus system and IEEE 118-bus system are employed to validate and evaluate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

BETO 2021 Peer Review - Biological Upgrading of Sugars (BUS) 2.3.2.105

The Biological Upgrading of Sugars (BUS) project directly targets the anaerobic conversion of lignocellulosic feedstocks into intermediate molecules readily upgradeable to fuel precursors. Recent efforts on the BUS project have a particular emphasis on the biological production of butyric acid, an intermediate that can be readily upgraded to sustainable aviation fuel, diesel blend-stocks, and high value chemicals. The BUS project approaches this direction through a combination of strain engineering, fermentation process engineering, development of novel separations technologies, and the design and build of pilot scale systems. Our ultimate project goal is to develop an integrated cost-effective process at pilot scale to achieve DOE's MYPP targets of $2.50/GGE. The major thrust of the BUS project over the last project cycle was on the development of integrated processes surrounding the anaerobic production of carboxylic acids using diverse Clostridium species. We developed and expanded genetic tools for several Clostridium species and rewired microbial metabolism in an attempt to maximize substrate utilization and flux towards butyric acid. We designed and built novel bioreactors with an in situ product recovery system enabling the biological production and recovery of highly purified acids. We leveraged this system to generate 100s of grams of acid from corn stover hydrolysate. In this presentation we highlight data surrounding our proposed process and accompanying results from technoeconomic and life-cycle analyses of our integrated process. Finally, we detail plans of our pilot scale reactor system that is in process and discuss our future routes towards achieving economically viable and sustainable diesel and jet blendstocks.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Foothill Transit Battery Electric Bus Evaluation (Final Report)

This report summarizes results of a battery electric bus (BEB) evaluation at Foothill Transit, located in Southern California. Foothill Transit began a demonstration of three Proterra BEBs in October 2010 to evaluate the battery technology and determine if the BEBs could meet Foothill Transit’s service requirements. Since that pilot project, the agency has added 31 BEBs to its fleet. Foothill Transit is collaborating with the California Air Resources Board (CARB) and the U.S. Department of Energy’s (DOE’s) National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The focus of the evaluation is to compare performance and cost of the BEBs to that of conventional technology in similar service and track progress over time. This report summarizes the results of the BEB and baseline fleets through December 2020.

25 ENERGY STORAGE↗

Automated Transit Fleet Electrification Planning in Response to Route Dynamics, Vehicle Utilization, and Local Climate

Transit electrification is difficult, requiring the consideration of many factors including route dynamics, vehicle utilization, and local ambient temperatures. Incumbent planning tools typically rely upon static vehicle efficiency numbers which do not consider local factors specific to each fleet. This paper summarizes a collaboration between NREL and Microgrid Labs, which produced an automated sizing tool capable of producing vehicle battery and motor sizing for drop-in electrification. Furthermore, the workflow also exports the electric-vehicle supply equipment needed to support fleet electrification. The paper summarizes the model theory and includes a sample pilot study performed in support of the Via Mobility transit fleet.

33 ADVANCED PROPULSION SYSTEMS↗

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗

Modifying Network Guided Vehicle for Repeatable EcoCAR ACC Energy Testing

The newest iteration of the Department of Energy (DOE) Advanced Vehicle Technology Competitions is the EcoCAR Mobility Challenge. In this paper, ANL and HORIBA MIRA collaborate to propose and pilot a test method that enables controlled, repeatable track-based energy consumption testing of semi-autonomous features. The testing was performed at MIRA’s proving ground facility in Nuneaton, UK, using their Network Guided Vehicle (NGV) connectivity and automation test platform. The NGV served as a repeatable lead vehicle following prescribed drive traces around two different track circuits while the host vehicle under test, a Honda Civic with full speed range Adaptive Cruise Control, followed behind. Over the course of a two day test, multiple iterations of certification and custom EPA drive traces were performed on track, demonstrating the viability of a two vehicle energy test. Results were analyzed to assess NGV lead vehicle performance in following the prescribed cycle using SAE J2951 standard calculations in an effort to quantify how repeatably and accurately the lead vehicle followed the trace. Host vehicle energy consumption was assessed using both vehicle CAN bus monitoring and an on-board fuel flow meter.

ACC↗

Advanced truck and bus radial materials for fuel efficiencies (Final Report)

PPG Industries, Inc. and Bridgestone Americas Tire Operations (BATO) propose to develop a novel surface-modified silica technology and demonstrate 4-6% improved fuel efficiency of Truck and Bus Radial (TBR) tires built from the technology. The proposed fuel efficiency increase will be achieved while maintaining or improving tear strength and tread wear. During rubber mixing, distributing silica in the rubber matrix is a challenge. This is because silica has a very polar surface, while rubbers have little polarity. It was hypothesized that surface treatments could cover part of the surface by hydrophobic groups, and reduce the surface polarity, thus helping to wet the silica with rubber during mixing and improving silica dispersion. During the project, the effect of different silica surface treatments on the surface energy of silica were determined, and related to the silica dispersion in rubber compounds. The results demonstrated that reducing the surface energy of silica samples improved dispersion in rubber compounds. Also, the preference for silica to migrate to the different phases in polymer blends was determined. The studies performed in binary polymer blends showed that carbon black has a preference to distribute in the different polymer phases in the order: SBR>BR~NR. Commercially available silica samples (treated and untreated) showed a preference in the order of SBR>NR>BR. Finally, the silica prototypes showed a preference in the order SBR=NR>BR. The knowledge gained regarding dispersion of treated silicas in rubber compounds was used to perform a series of studies to develop a silica – rubber compound combination with optimum performance for TBR treads. Initially, two silica prototypes (BXR-990 and BXR-991) were developed and used for a tire build at BATO’s tire plant in Warren County, TN. Results were evaluated and further silica and compound optimization was performed, prior to a final tire build. Manufacturing of the final silica prototype (BXR-1006) for the final tire build was performed at the PPG Silicas Pilot Plant in Monroeville, PA. Afterwards, experimental tires with silica-filled treads and control tires with carbon black-filled treads were built at BATO’s Warren County tire plant. The experimental TBR tires with silica-filled treads achieved the project goals for lab performance indicators, tread hardness and tear strength. The tires showed a 2.2% improvement in fuel efficiency compared to the control tires. While this improvement is lower than the 4% goal set initially, the improvement is significant and there are indicators that up to a 5% improvement in fuel efficiency could be achieved. This is supported by the confirmation of the validity of the fuel efficiency indicators made at the beginning of the project, and by the improvement in hysteresis and rolling resistance from tires built earlier in the project. The experimental tires produced using the BXR-990 silica prototype showed 47% improvement in tan δ at 60°C and 16% improvement in rolling resistance. Based on the results obtained, it is valid to estimate that the tires built with BXR-990 could provide around a 5% improvement in fuel efficiency, should we perform a fuel efficiency test. Tire wear for the experimental tires was 31% worse than for the control tires with the carbon black-filled tread compound. Other tools and further analysis of factors affecting wear are necessary to be evaluated to produce a silica tire with wear comparable to carbon black. Experimental and control tires were provided to the DOE for independent testing.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of Brine Management for Geologic Carbon Sequestration

Geologic carbon sequestration (GCS) is the injection of carbon dioxide (CO 2 ), typically captured from stationary emission sources, into deep geologic formations to prevent its entry into the atmosphere. Active pilot facilities run by regional United States (US) carbon sequestration partnerships inject on the order of one million metric tonnes (mt) CO 2 annually while the US electric power sector emits over 2000 million mt-CO 2 annually. GCS is likely to play an increasing role in US carbon mitigation initiatives, but scaling up GCS poses several challenges. Injecting CO 2 into sedimentary basins raises fluid pressure in the pore space, which is typically already occupied by naturally occurring, or native, brine. The resulting elevated pore pressures increase the likelihood of induced seismicity, of brine or CO 2 escaping into potable groundwater resources, and of CO 2 escaping into the atmosphere. Brine extraction is one method for pressure management, in which brine in the injection formation is brought to the surface through extraction wells. Removal of the brine makes room for the CO 2 and decreases pressurization. Although the technology required for brine extraction is mature, this form of pressure management will only be applicable if there are cost-­effective and sustainable methods of disposing of the extracted brine. Brine extraction, treatment, and disposal may increase the already substantial capital, energy, and water demands of Carbon dioxide Capture and Sequestration (CCS). But, regionally specific brine management strategies may be able to treat the extracted water as a source of revenue, energy, and water to subsidize CCS costs, while minimizing environmental impacts. By this approach, value from the extracted water would be recovered before disposing of any resulting byproducts. Until a price is placed on carbon, we expect that utilities and other CO 2 sources will be reluctant to invest in capital intensive, high risk GCS projects; early technical, economic, and environmental assessments of brine management are extremely valuable for determining the potential role of GCS in the US. We performed a first order feasibility and economic assessment, at three different locations in the US, of twelve GCS extracted-­water management options, including: geothermal energy extraction, desalination, salt and mineral harvesting, rare-­earth element harvesting, aquaculture, algae biodiesel production, road de-­icing, enhanced geothermal system (EGS) recharge, underground reinjection, landfill disposal, ocean disposal, and evaporation pond disposal. Three saline aquifers from different regions of the US were selected as hypothetical GCS project sites to encompass variation in parameters that are relevant to the feasibility and economics of brine disposal. The three aquifers are the southern Mt. Simon Sandstone Formation in the Illinois Basin, IL; the Vedder Formation in the southern San Joaquin Basin, CA; and the Jasper Interval in the eastern Texas Gulf Basin, TX. These aquifers are candidates for GCS due to their physical characteristics and their close proximity to large CO 2 emission sources. Feasibility and impacts were calculated using one mt-­CO 2 injected as the functional unit of brine management. Scenarios were performed for typical 1000MW coal-­fired power plants (CFPP) that incurred an assumed 24 percent carbon capture energy penalty (EP), injected 90 percent of CO 2 emissions (~9 million mt-­ CO 2 injected annually), and treated extracted water onsite. Net present value (NPV), land requirements, laws and regulations, and technological limits were determined for each stage of disposal, and used to estimate feasibility. The boundary of the assessment began once extracted water was brought to the surface, and ended once the water evaporated, was injected underground, or was discharged into surface water bodies. Results of the assessment were generated, stored, and analyzed using Microsoft Excel spreadsheets and ESRI Geographical Information System (GIS) maps. Conclusions about the relative benefits and impacts of alternative brine-­management strategies were highly sensitive to local climate and weather, and aquifer water chemistry. The NPV of certain scenarios ranged from -­$50/mt-­CO 2 (a cost) to +$10/mt-­CO 2 (revenue). The land footprint of the scenarios in this study ranged from <1 km 2 to 100 km 2 . Brine extraction as a pressure management tool for GCS has potential for improving the economics and for minimizing the environmental impacts of CCS. In order to maximize this potential, careful analysis of each saline aquifer and region must be conducted to determine a regionally appropriate brine use sequence (BUS) at the time of site selection. Models that use GIS will be essential tools in determining such sequences for individual CFPP. Future studies that perform risk and life cycle assessments (LCA) of BUS scenarios, incorporate additional impact metrics into the BUS model, and enhance the temporal sensitivity of the model would improve the robustness of this regional assessment method.

54 ENVIRONMENTAL SCIENCES↗