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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

Commercial building loads providing ancillary services In PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

MacDonald, Jason↗

Retail Hydrogen Station Reliability Status and Advances

One of the most vital emerging commercial markets for hydrogen is fuel cell-powered mobility including cars, trucks, and buses. These vehicles are refueled via a network of hydrogen fueling stations, with the highest number of U.S. stations being in California. The numbers of both fuel cell electric vehicles (FCEVs) and hydrogen stations have increased in the last two years, with anecdotal information from FCEV drivers indicating that station reliability is hurting the consumer acceptability of FCEV technologies. Therefore, this study benchmarks the current state of hydrogen station reliability in practice and presents on-going research that is investigating the failures that are contribute to hydrogen station reliability issues. This is accomplished with an analysis of operation, safety, and maintenance data from hydrogen stations and fuel cell electric vehicles to benchmark the maintenance and failure of hydrogen stations and their components. This analysis, of over 5,000 station maintenance events, presents the leading maintenance categories and failure rates, and is a prerequisite to the development of data-driven reliability improvement plans. We present a reliability growth analysis and on-going research into the root causes of failure for dispensers, a particularly failure-prone subsystem.

08 HYDROGEN↗

Stabilizing lithium-metal electrodes with polymer coatings

Increasing the energy density of batteries can accelerate the deployment of electric vehicles, expand the utilization of renewable energy and, in turn, reduce greenhouse gas emissions. Different from commercially available lithium-ion batteries, high-energy-density lithium-metal batteries use metallic lithium instead of graphite as the negative electrode. Furthermore, the commercialization of lithium-metal batteries is hindered by the electrochemical instability of lithium metal. Polymer coatings have shown promise in addressing issues related to each step of heterogeneous lithium deposition. Here we summarize the current understanding of key design principles and highlight relevant coating compositions. Moreover, we discuss high-performing coating–electrolyte pairs and provide an outlook on interface design for novel electrolytes.

Batteries↗

Geographic Information System Mapping Tool for Rainwater Harvesting in the United States

The Rainwater Harvesting Tool is a publicly available web-based geographic information system tool developed using geospatial analysis in combination with historic ZIP Code level monthly average precipitation and evapotranspiration data across the United States to help select potential locations for harvesting rainwater. Rainwater harvesting can provide a key source of alternative water for a variety of uses including landscape irrigation, vehicle wash, cooling tower makeup, dust suppression, and toilet flushing. Rainwater harvesting can help support institutional, commercial, and residential buildings in diversifying water sources and offset the use of freshwater. This tool aims to help organizations strategically target locations to implement rainwater harvesting systems. The metric used in the tool is called the rainwater harvesting potential, which is a normalized metric, measured in inches per year. The rainwater harvesting potential describes the amount of rainwater that can be reasonably collected and stored at a specific location. This metric was used to rank areas delineated by ZIP Codes across the US, from lowest to highest to show the relative availability of rainwater for harvesting. Two mapping layers are included in the tool that show the general rainwater harvesting potential for all applications and a layer that specifically shows the potential for harvesting rainwater to supply irrigation The Rainwater Harvesting Tool allows users to view overall trends across the United States, while also allowing the user to zoom in to a scale where ZIP Code boundaries are clearly delineated. The tool can be used to help organizations with buildings located in multiple regions to strategically identify where to install rainwater harvesting systems and prioritize locations that may be optimal for rainwater harvesting.

47 OTHER INSTRUMENTATION↗

Energy Storage Market Transformation Through Stored Energy Targets

Aggressive energy decarbonization targets will require the rapid deployment of renewable energy in the U.S. in coming years. As the amount of variable generation on the grid grows, there will be an increasing need for long-duration energy storage (LDES) technologies to maintain grid reliability. Meeting that need will require a suite of technology alternatives with different capabilities. Many of these alternatives, however, are in a nascent state and face significant commercialization challenges. In the last decade, 10 U.S. states have enacted energy storage mandates as a vehicle for market transformation to accommodate energy storage. Those mandates, however, fail to send appropriate investment signals for LDES technologies because they are based on energy storage capacity and treat all technologies the same, regardless of duration. This paper explores the idea of replacing capacity-based storage procurement targets with stored energy targets, which would be technology-neutral policies designed to enable the market transformation necessary to support a competitive LDES industry.

Twitchell, Jeremy B.↗

Model Predictive Control-Based Trajectory Shaper for Safe and Efficient Adaptive Cruise Control

Recent studies show that commercially-available adaptive cruise control (ACC) systems are string-unstable, indicating that ACC-driven vehicles amplify speed fluctuations from downstream traffic and induce stop-and-go waves. Moreover, it is challenging to revise the original control algorithm of an ACC system to achieve string stability due to its internal complexity and powertrain uncertainties. To achieve desired control performance given a string-unstable ACC system and circumvent revising the original control algorithm, this study proposes a model predictive control-based trajectory shaper (MPC-TS), which only modifies the sensor-measured trajectory information (i.e., position and speed) of the preceding vehicle. The proposed MPC-TS leverages the input shaping technique to generate reference trajectory to improve string stability, while incorporating tracking errors and vehicle acceleration/deceleration magnitude in the MPC cost function and constraining fluctuations of vehicle speed and spacing to ensure desired car-following performance. Numerical experiments validate the control performance of ACC with the proposed MPC-TS in terms of string stability, safety, traffic efficiency, and comfort.

Zhou, Anye↗

Investigating the Particle Growth in Bimodal Pt/C Catalysts by In-Situ Small-Angle X-ray Scattering: Challenges in the Evaluation of Stress Test Protocol-Dependent Degradation Mechanisms

The influence of different combinations of accelerated stress test (AST) protocols simulating load-cycle and start/stop conditions of a proton exchange membrane fuel cell (PEMFC) vehicle is investigated on a bimodal Pt/C catalyst. The bimodal Pt/C catalyst, prepared by mixing two commercial catalysts, serves as a model system and consists of two distinguishable size populations. The change in mean particle size was investigated by in situ small-angle X-ray scattering (SAXS). The comparison to the reference catalysts, i.e., the two single-size population catalysts, uncovers the presence of electrochemical Ostwald ripening as a degradation mechanism in the bimodal catalyst. Increasing the harshness of the applied AST protocol combinations by faster changing between load-cycle or start/stop conditions, the particle size of the larger population of the bimodal catalyst increases faster than expected. Surprisingly, the change in mean particle size of the smaller size population indicates a smaller increase for harsher AST protocols, which might be explained by a substantial electrochemical Ostwald ripening.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DSO+T: Integrated System Simulation (DSO+T Study: Volume 2)

This report summarizes an integrated co-simulation model used by the Distribution System Operator with Transactive (DSO+T) study to represent an electrical generation, delivery, and end-load systems for the purposes of assessing the viability and value proposition of transactive energy coordination of flexible assets versus a business-as-usual case. The integrated co-simulation model includes the bulk generation and transmission system, including the day-ahead and real-time scheduling and dispatch of thermal generators. Forty distribution system operators were modelled in detail, including tens of thousands of residential and commercial buildings and their flexible end-loads. These included HVAC systems, residential water heaters, electric vehicles, and stationary, behind-the-meter, batteries. Both wholesale market and end-load results for the business-as-usual case are presented and compared to actual ERCOT system data to assess the accuracy and representativeness of the resulting model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Chemical contributions to silicon anode calendar aging are dominant over mechanical contributions

Silicon (Si) anodes are a promising candidate for increasing the energy density of lithium (Li)-ion batteries for electric vehicles. However, they have recently been identified as having poor calendar life that is insufficient for commercial needs, in addition to the well-known issue of their poor cycle life resulting from large volume expansion. Here, a specially designed protocol with variable rest periods between intermittent cycling is used to evaluate the impact of the mechanical disruption of Si and solid electrolyte interphase (SEI) from cycling on calendar aging measurements. Si was found to undergo more mechanical degradation during calendar aging with intermittent cycling than graphite. However, Si anode capacity fade was still dominated by time, especially for rest periods greater than or equal to 1 month between cycling. Postmortem dQ/dV half-cell analysis indicated this was mainly due to Li inventory loss and an increase in electrode resistance. Isothermal microcalorimetry further demonstrated that Si passivation is more disrupted than graphite passivation with intermittent cycling and suggested that there may be a chemical buildup of a detrimental species in the electrolyte, leading to a large spike in heat after the Si and SEI are disrupted by cycling.

25 ENERGY STORAGE↗

Extracting energy from ocean thermal and salinity gradients to power unmanned underwater vehicles: State of the art, current limitations, and future outlook

Thermal gradient energy-generation technologies for powering unmanned underwater vehicles (UUVs) or autonomous sensing systems in the ocean are mainly in the research development phase or commercially available at a limited scale, and salinity-gradient energy-generation technologies have not been adequately researched yet. The demand for self-powered UUVs suitable for long-term deployments has been growing, and further research related to small-scale ocean gradient energy systems is needed. In this study, we conducted a comprehensive review about harvesting energy from ocean thermal or salinity gradients for powering UUVs, focusing on gliders and profiling floats. Thermal gradient energy systems for UUVs based on phase change materials (PCM) cannot provide the energy required for powering autonomous sensing systems because of the systems' low energy conversion efficiency. Besides reducing energy consumption by developing more efficient electrical-mechanical systems, enhancing the thermal conductivity of the PCMs may help address this challenge by increasing the power generation rate of the UUVs. Several other emerging technologies, such as thermoelectric generators, shape memory alloys, and small-scale thermodynamic cycle systems, have shown potential for powering UUVs, but they are still only at the laboratory testing or conceptual design phase. The most advanced power generation technologies based on salinity gradients, reverse electrodialysis and pressure-retarded osmosis, are still not economically viable for large-scale deployment, mainly because of the high cost of the components required to operate in harsh saline environments. Our feasibility evaluation showed that existing salinity gradient power generation technologies are not directly feasible for powering UUVs in the open ocean.

16 TIDAL AND WAVE POWER↗

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Recycling Rare Earth Elements from End-of-Life Electric and Hybrid Electric Vehicle Motors

In this paper, we propose a superstructure-based approach to finding the optimal pathways for recovering rare earth elements in their commercialized rare earth oxide form from end-of-life EV and HEV motors. The proposed superstructure was modeled as a MILP optimization problem, selecting the net present value as the objective function. Whenever possible, costing data taken from the literature was used to inform this mode. However, due to the novelty of this research area data were often not available thus requiring the generation of flowsheets that were implemented in Aspen Plus.

Laliwala, Chris↗

Progress of Nanotechnology for Lithium-Sulfur Batteries

Lithium-Sulfur (Li-S) battery has been proposed and investigated since the 1960s as an effective energy storage device via reversible electrochemical reactions. As the fast development and commercialization of Li-ion battery (LIB) technology kept moving forward, no breakthroughs have been attained to solve critical technical issues facing Li-S batteries during the following decades. In the year 2000s, Li-S batteries reattracted significant interests in the research field owing to their low-cost advantages, high theoretical specific energy of 2600 Wh kg -1 , which is at least 3 times higher than the current LIB technology. The low-cost and high abundance of sulfur (i.e., the cathode active material), make Li-S batteries more appealing than LIBs given the fact that the latter use critical materials such as cobalt and nickel in the manufacturing of the cathodes. Moreover, the high-energy and low-cost features make the Li-S battery a promising energy storage technology in practical applications such as portable devices, electric vehicles, and grid storage when coupled with the harvesting of solar or wind renewable energies. For example, since 2007, SION Power Corporation (Tucson, USA) and Oxis Energy (UK) made progress towards the commercialization of Li-S batteries with products showing specific energies over 350 Wh kg -1 for powering electric vehicles. To be on a par with the current LIB technology, the ultimate goal of achieving 500 Wh kg -1 for Li-S battery will make it more competitive for widespread commercialization.

Li, Mengya↗

Opening twisted polymer chains for simultaneously high printability and battery fast-charge

Fast-charging is key to the widespread adoption of battery-based electric vehicles. However, improving fast-charging through architecture optimization is expensive. To reduce costs and expand to commercialization, we applied roll-to-roll screen printing technology to create channels and decrease the tortuosity of electrodes. For the first time, this work successfully opened twisted polymer chains within high-solid-content inks to improve their screen printability and battery performance of as-printed electrodes. With LiNi 0.6 Mn 0.2 Co 0.2 O 2 as active materials, the 60% solid content ink presents superior screen printability after opening the twisted binder chains. As-printed electrode exhibits 33% higher charge capacity at 6 C than printed electrode with chains twisted ink at mass loading of 6.5 mg/cm 2 . Furthermore, coarse-grained molecular dynamics simulations are performed to study the underlying mechanism systematically. In conclusion, the new ink preparation procedure provides a scalable, effective strategy for manufacturing screen-printable battery ink and promotes screen-printed electrode technology.

25 ENERGY STORAGE↗

100+ RON Gasoline Blendstock for High Efficiency, Low Emissions (CRADA 493)

The PNNL/LanzaTech alcohol-to-Jet (ATJ) patented process converts ethanol from LanzaTech’s syngas fermentation process to low aromatic jet-range isoparaffins. Compounds are generated across a wide boiling range by the process. The project goal is to improve the viability of the ATJ process by increasing the RON of the gasoline fraction and determine what types of engines and vehicles can be fueled with this gasoline. PNNL experts’ team will investigate the impact of the process conditions and catalysts formulation on the blendstock composition in relation with the fuel properties. Co-optima capabilities for fuel properties measurements will be leveraged to assess the potential engines/ vehicles applications of the produced blendstock. A techno-economic-analysis will be conducted to assess the commercial viability of the process for generating a high RON gasoline-range fuel.

09 BIOMASS FUELS↗

Advanced Laboratory and Field Arrays (ALFA)/Lab Collaboration Project (LCP) for Marine Energy (Final Scientific/Technical Report)

The objective of the Advanced Laboratory and Field Arrays (ALFA) project was to reduce the Levelized Cost of Energy (LCOE) of Marine and Hydrokinetic (MHK) energy by leveraging research, development, and testing capabilities at Oregon State University, University of Washington, and the University of Alaska, Fairbanks. ALFA is a project within the Pacific Marine Energy Center (PMEC; formerly NNMREC), a multi-institution entity with a diverse funding base that focuses on research and development for marine renewables. The ALFA project aimed to accelerate the development of next-generation arrays of wave energy conversion (WEC) and tidal energy conversion (TEC) devices through a suite of field-focused R&D activities spanning a broad range of strategic opportunity areas identified in the Funding Opportunity Announcement: • Device and/or array operation and maintenance (O&M) logistics development; • High-fidelity resource characterization and/or modeling technique development and validation; • Array-specific component technology development (e.g. moorings and foundations, transmission, and other offshore grid components); • Array performance testing and evaluation; and • Novel cost-effective environmental monitoring techniques and instrumentation testing and evaluation. The objective of the Lab Collaboration Project (LCP) was to accelerate the development of next-generation marine energy conversion systems. The LCP aimed to achieve these project objectives in collaboration with the national laboratories by: • Developing concept generation and assessment tools; • Improving access to existing testing resources; • Validating collision risk models between fish and turbines; and • Advancing analysis and simulation capabilities for wave-WEC interactions and PTO analysis in nonlinear ocean waves. The ALFA portion of the project was comprised of six overarching technical tasks: • Task 1: Debris Modeling, Detection and Mitigation; • Task 2: Autonomous Monitoring & Intervention; • Task 3: Resource Characterization for Extreme Conditions; • Task 4: Robust Models for Design of Offshore Anchoring and Mooring Systems; • Task 5: Performance Enhancement for Marine Energy Converter (MEC) Arrays; and • Task 6: Evaluating Sampling Techniques for MHK Biological Monitoring. The LCP was divided into four overarching technical tasks: • Task 7: Project Management and Reporting • Task 8: Novel Design and Assessment Methodologies for Wave Energy Converter Design (Wave- SPARC) • Task 9: Testing Access for Commercial Marine Renewable Energy Technology Developers • Task 10: Quantifying Collision Risk for Fish and Turbines • Task 11: Nonlinear Ocean Waves and PTO Control Strategy Each ALFA/LCP task listed above functioned as a separate and discreet project. A final Technical Report was written for each individual task and these reports were uploaded to OSTI, after receiving DOE approval. The following document is a compilation of each of these final, approved reports arranged as individual chapters.

13 HYDRO ENERGY↗

GT Flex: A Coordinated Multi-Building Pilot Study

Buildings are a significant and untapped resource for providing utility electric grid services. Recent studies have estimated that buildings could reduce the peak demand on the electric grid in the U.S. by almost 25% through effective combinations of energy efficiency (EE) measures and load flexibility strategies (Langevin et al. 2021). The U.S. Department of Energy (DOE) has established a goal to triple energy efficiency and demand flexibility in both residential and commercial sections by 2030 compared to 2020 levels (Satchwell et al. 2021). Such findings place buildings alongside electric vehicles, photovoltaics, electric batteries, and other distributed energy resources (DERs) as primary technologies needed for supporting high renewable energy generation grids. Coordinating and optimizing multiple buildings and other DERs is more beneficial and valuable when compared with individual buildings and DERs operating as siloed resources, uncoordinated with others (Olgyay et al. 2020). A pilot study at the Georgia Institute of Technology (GIT) was conducted to evaluate value propositions of a multi-building scale project seeking carbon reduction, energy efficiency and grid-interactive capabilities, by demonstrating the means by which stakeholders can determine the technical and financial merits of grid-interactivity and energy efficiency technologies coordinated across multiple assets. The study focused on analyzing technical feasibility of deploying thermal load flexibility strategies at the multi-building scale, coordinated to not exceed existing infrastructure constraints at the pilot site. Results show that campus can provide 3-3.5 MW of potential load shed over a 4-hour event window through coordinated dispatch of thermal cooling load flexibility without exceeding existing infrastructure capacities. Under future high renewable scenarios, this thermal flexibility resource is also valuable when coordinated to reduce curtailment of intermittent renewables. Economic analyses were performed to effectively communicate various value propositions of grid-interactive and efficient building (GEB) thermal flexibility strategies. Load flexibility presents a financial value proposition to the campus today. By conducting rationalized, coordinated dispatch in response to real time price (RTP) fluctuations, the campus can benefit materially from daily price arbitrage. The RTP signal acts as an aggregating mechanism between the utility and customer to call on demand flexibility resources, with a large portion of the benefit deriving from a relatively small number of days. Realizing and maximizing this benefit with thermal load flexibility requires careful attention to the timing of pricing signals and parameterization of dispatch to overcome efficiency penalties. Grid value and signals are expected to evolve over time, and thermal load flexibility shows potential to adapt dispatch logic to support intermittent renewable generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗