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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Investigation of Sub‐Bandgap Emission and Unexpected n‐Type Behavior in Undoped Polycrystalline CdSe x Te 1‐x

Abstract Se alloying has enabled significantly higher carrier lifetimes and photocurrents in CdTe solar cells, but these benefits can be highly dependent on CdSe x Te 1‐x processing. This work evaluates the optoelectronic, chemical, and electronic properties of thick (3 µm) undoped CdSe x Te 1‐x of uniform composition and varied processing conditions (CdSe x Te 1‐x evaporation rate, CdCl 2 anneal, Se content) chosen to reflect various standard device processing conditions. Sub‐bandgap defect emission is observed, which increased as Se content increased and with “GrV‐optimized CdCl 2 ” (i.e., CdCl 2 anneal conditions used for group‐V‐doped devices). Low carrier lifetime is found for GrV‐optimized CdCl 2 , slow CdSe x Te 1‐x deposition, and low‐Se films. Interestingly, all films (including CdTe control) exhibited n‐type behavior, where electron density increased with Se up to an estimated ≈10 17 cm −3 . This behavior appears to originate during the CdCl 2 anneal, possibly from Se diffusion leading to anion vacancy (e.g., V Se , V Te ) and Cl Te generation.

14 SOLAR ENERGY↗
DOE OSTI2023

Introduction of a Variable Inductance Transformer for the Design of Resonant Power Converters

Magnetic integration is a hot topic in power electronics that concerns the use of a transformer’s leakage and magnetizing inductances purposefully in isolated power electronic converters, thereby giving the opportunity to save the cost and footprint of any additional inductor. This is of prime interest, especially in CLLLC resonant converters which require up to three inductors. For a complete integration of these inductances, the concept of a variable inductance transformer (VIT) is introduced in this thesis. A VIT is an adaptive magnetic structure that facilitates an easy adjustment of both magnetizing and leakage inductances to meet their desired values. However, for a more promising design, an accurate estimation of these inductances is necessary. While the evaluation of magnetizing inductance is quite straightforward, the calculation of leakage inductance is rather convoluted, because the leakage inductance is influenced by both the winding layout and the operating frequency. In this thesis, three new semi-analytical methods for calculating the frequency-independent leakage inductance, and a novel semi-analytical method for evaluating the frequency-dependent leakage inductance are proposed. These methods can calculate the respective leakage inductances of a VIT within an outstanding ±5% uncertainty. Finally, a bidirectional CLLLC resonant dc-dc converter is investigated for the constant current constant voltage (CCCV) charging of the next-generation 900 V traction battery of an electric vehicle. A new voltage gain equation is derived for designing the CLLLC resonant tank, and a small-signal model is presented for designing the variable-frequency feedback controller. Furthermore, a new methodology to design a VIT is developed to overcome the challenges associated with small coupling coefficients and guarantee a complete magnetic integration of the tank inductances. All theoretical results presented herein are verified through simulations and experiments performed on hardware prototypes designed in the lab.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Caldera Infrastructure Charge Module (ICM)

Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as "Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2026

Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers (Final Technical Report)

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB) and GTI Energy (GTI) for award “DE-FE0031969: Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers” sponsored by the U.S. Department of Energy (DOE). The objective of this project is to develop an innovative sorbent structure of trapped small amines in HNC embedded in PEF for DAC. This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An innovative sorbent structure of trapped small amines in hierarchical nanoporous capsules (HNC) embedded in porous electrospun fibers (PEF) was developed for direct air capture (DAC). This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An interfacial polymerization process was developed, which utilized loaded amines inside mesoporous silica and trimesoyl chloride (TMC) dissolved in organic solvents as the precursors, to generate a polyamide (PA) coating layer on mesoporous silica and thus trap amines. Reaction conditions, including TMC concentration, organic solvents, reaction time, etc., for interfacial polymerization were optimized to effectively trap loaded amines, and cyclic heating-cooling operation was conducted to evaluate the coating quality. Larger pore volume mesoporous silica was also synthesized to increase amine loading and thus increase CO 2 capacity. The optimized sorbent material exhibited CO 2 capacity as high as 4.88 mmol/g under humid DAC conditions and negligible loss (<1%) during 10 cyclic heating-cooling operations. The optimized PA-coated sorbent also showed fast adsorption and desorption kinetics, with <20% t1/2 increase compared to uncoated sorbent. PEF fabrication conditions, including organic solvents for dissolving core and shell polymers, voltage, distance from the nozzle to the collection panel, etc. were adjusted to better incorporate HNC. After incorporating the optimized sorbent material into PEF, the structured sorbent had a CO 2 capacity of approximately 4.0 mmol/g under humid DAC conditions, with capacity loss of 0.17% per cycle and t1/2 increase less than 10%. A techno-economic analysis (TEA) for the process design for a DAC system based on our developed sorbent structure of trapped small amines in HNC embedded in PEF was conducted. The process design included process description and major equipment sizing and energy and mass balances in addition to scale-up research results and estimated capture cost. Aspen Adsorption Simulator was used to fit the experimentally measured breakthrough curves and extract equilibrium and kinetic data of the optimized sorbent. Our results indicated that for a DAC plant with CO 2 productivity of 3,000 tonne/year, the levelized cost of CO 2 capture was $\$$612/tonne, with the largest contribution of 44.33% from the fixed operation cost. Increasing CO 2 productivity, while maintaining similar fixed operation cost, is expected to significantly reduce the CO 2 capture cost. A sensitivity study was also conducted to understand the influence of total plant cost, sorbent cost, CO 2 concentration in the feed, sorbent mat lifetime, sorbent regeneration electricity, and adsorption blower pressure drop on the levelized cost of CO 2 capture, revealing a capture cost range of $\$$520-870/tonne.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intensity Modulated Fiber Optic Sensor: A Novel Grid Measurement Unit

This paper presents a novel approach to physical displacement-based power grid measuring via an Intensity Modulated Fiber Optic Sensor (IMFOS). An IMFOS utilizes one fiber to transmit the intensity modulation light from its Electro-Optic controller to a fiber optic probe. The power grid voltage and current can induce physical displacements in transducers via the piezoelectric effect and the Lorentz law, respectively, which then result in a distance change between the optical probe and the reflective surface of the transducers. In parallel, multiple fibers are used to collect the reflective light for electro-optic conversion. Furthermore, a National Instruments-based characterization platform is set up for performance evaluation. Here, the testing result demonstrates that the IMFOS is immune to the inherent DC and low-frequency saturation issues prevalent in conventional potential and current transformers. Finally, the IMFOS is implemented in a Universal Grid Analyzer to illustrate its applicability for phasor estimation in actual power grids.

42 ENGINEERING↗
DOE OSTI2026

Findings from Large Bench-Scale Testing of Denitration Electrolyzers for the EDCGe Project

This report highlights the key findings and outcomes relevant to the processability of waste supernatant at Hanford using a denitration electrolyzer. The Electrosynthesis Company issued a Phase 1 report to the Savannah River National Laboratory (SRNL), summarizing the evaluation of large bench-scale denitration electrolyzers to support the electrochemical denitration and caustic generation (EDCGe) project. The Electrosynthesis Company’s report (attached as Appendix A) provides insights into the initial steps required to implement an electrolyzer system at Hanford. Phase 1 experiments focused on validating the denitration electrolyzer’s performance, operating parameters, and reaction products. The robustness of the electrochemical denitration process was demonstrated by two electrolyzer flow cell systems (a 100 cm 2 ElectroCell MP and a 150 cm 2 NESI NS01 cell), both of which achieved significant nitrate and nitrite removal (>50%) with a current efficiency of ~95% for both systems. Higher current densities (500 mA cm –2 ) improved nitrate and nitrite removal rates compared to lower current densities (333 mA cm –2 ), while maintaining a current efficiency of ~94%. The NS01 cell achieved a nitrate species removal rate of ~0.41 mol h –1 at 5 kA m –2 (equiv. to 500 mA cm –2 ). The primary reaction product was ammonia (NH 3 ), constituting 78.3–91.6% of the products (excluding OH – formation). NH 3 was predominantly retained in the catholyte liquid phase rather than being off-gassed. Additionally, the NS01 cell reported an NH 3 generation rate of ~0.36 mol h –1 at 5 kA m –2 . Other gas formation included ~7% N 2 , ~7% H 2 , and trace amounts of N 2 O. The estimated power requirement (extrapolated from the 0.015 m 2 cell data) for a full-scale denitration electrolyzer is approximated to be ~1.6 MW (DC-only) to treat 50% of nitrate and nitrite in a waste stream and generates ~2.1 kmol h –1 of NH 3 with an initial concentration of 4 M NO 3 – /NO 2 – at 300 gal h –1 . Simulated waste containing aluminate, carbonate, oxalate, and halogens exhibited no adverse effects on denitration performance. A preliminary experiment comparing alkaline anolyte (5 M NaOH) with a nickel based anode to acidic media (2 M H 2 SO 4 ) with a DSA-O 2 anode showed a lower operating voltage and generated less H 2 than the acid media. Maintaining a stable 5 M OH – concentration in the anolyte through periodic additions of caustic did not significantly impact denitration performance. This operational mode will be required for long-term experiments. All the experiments demonstrated that electrochemical denitration is a promising approach for treating nitrate and nitrite in simulated waste streams, achieving significant conversion and robustness across varying experimental conditions and electrochemical cell configurations. Lastly, the ability to generate a nearly pure NH 3 stream may prove advantageous for processing at other locations within the Hanford site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Effect of Coaxial Electrode Geometry on the Electric Field Enhancement Factor for a High Voltage Vacuum Gap

We present an experimental analysis of the change in the electric field enhancement factor with varying gap size and penetration depth (P.D) of cathode into anode for a coaxial vacuum gap, diagnosed using Fowler–Nordheim analysis and optical imaging via scanning electron microscope (SEM) and time integrated Digital single lens reflex camera (DSLR). Data were collected on the Coaxial Gap Breakdown Machine (240 A, 25 kV, 150 ns, 0.1 Hz). Experiments using five different gap sizes at nine different P.Ds are compared over runs comprising 50 shots for each case. The results show a strong link between enhancement factor and gap size, with P.D and surface topology. For large gap sizes, 150, 330, and 700 μm, the average enhancement factor value increases with increasing P.D. For smaller gap sizes, 50 and 100 μm, the average enhancement factor decreases with P.D. SEM imaging before and after plasma formation for each gap size allows for quantifying surface finish, microprotrusion growth, average blast diameter, and an estimation of the surface area breakdowns occupy. Time integrated DSLR imaging analysis of the gap at each shot allows for a determination of the distribution of breakdowns about the circumference of the gap for each case tested. Here, the Fowler–Nordheim analysis allows for a quantitative analysis of the surface roughness of all gap sizes tested. Results show that for large gap sizes, the gap geometry and increasing area of breakdown is the main cause for increasing average enhancement factor. For small gap sizes, the dominant driving factor for small average enhancement factors—that subsequently decrease with P.D—is significant changes in surface topology due to an increased number of breakdowns.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Hot-Carrier Extraction in Nanowire-Nanoantenna Photovoltaic Devices

Nanowires bring new possibilities to the field of hot-carrier photovoltaics by providing flexibility in combining materials for band engineering and using nanophotonic effects to control light absorption. Previously, an open-circuit voltage beyond the Shockley–Queisser limit was demonstrated in hot-carrier devices based on InAs–InP–InAs nanowire heterostructures. However, in these first experiments, the location of light absorption, and therefore the precise mechanism of hot-carrier extraction, was uncontrolled. In this study, we combine plasmonic nanoantennas with InAs–InP–InAs nanowire devices to enhance light absorption within a subwavelength region near an InP energy barrier that serves as an energy filter. From photon-energy- and irradiance-dependent photocurrent and photovoltage measurements, we find that photocurrent generation is dominated by internal photoemission of nonthermalized hot electrons when the photoexcited electron energy is above the barrier and by photothermionic emission when the energy is below the barrier. We estimate that an internal quantum efficiency up to 0.5–1.2% is achieved. Insights from this study provide guidelines to improve internal quantum efficiencies based on nanowire heterostructures.

14 SOLAR ENERGY↗
DOE OSTI2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Simplified calculation of the area specific impedance for solid-state battery design

Simplified algebraic area specific impedance (ASI) correlations have been developed for solid-state composite battery electrodes made of a single ion conducting electrolyte, conductive additive, and intercalation active material. Two ASI expressions were developed, one for short times ( i.e. , pulsed power operation) and another for the pseudo steady state operation (i.e., sustained discharge for energy estimation). A full electrochemical model based on porous electrode theory was developed to examine the accuracy of the simplified ASI expressions. The simplified expressions agree favorably with full model results over a wide range of parameters (i.e. , electrode thicknesses, electrolyte conductivities, solid-state diffusion coefficients, specific surface areas, etc.) and conditions (i.e. , C-rates, states of charge, and pulse times). Under most conditions, the error between the full model and the correlations is well below 7 %. Higher errors were observed for the pseudo steady state expression at high/ low states of charge where the assumption of uniform reaction distributions loses validity. Here, the short time ASI has higher error at low states of charge due to the nonlinearity of the open circuit voltage equation, which is assumed linear in the formulation of the simplified algebraic expression.

25 ENERGY STORAGE↗
DOE OSTI2021

BATPAC--VERSION 5.0

Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft¿ Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.

AHMED, SHABBIR↗
DOE OSTI2026

Intense cavitation-assisted electric discharge as a promising tool for water treatment

This study investigates interrelations between one-electrode Cavitation-Assisted Electric Discharge (CAED), two-electrode CAED, and recently discovered Intense CAED (I-CAED). The one-electrode CAED is a self-triggered nanosecond discharge with pulse energy in the micro-Joule range, which can be generated even by a DC voltage. I-CAED consists of a non-equilibrium part within a low-pressure cavitating region and a micro-spark traversing a liquid film. We hypothesize that CAED propagates from the high-voltage electrode as an ionization wave through bubbles of saturated vapor. Subsequently, the streamer-like discharges in the bubbles may form a continuous plasma channel. Inside the cavitating region, the plasma is strongly non-equilibrium, providing an ideal environment for generating chemically unstable species such as hydrogen peroxide (H 2 O 2 ). Plasma of I-CAED spark is characterized by high electron density and near-thermal equilibrium, emitting a continuous ultraviolet spectrum. The combination of these different discharge parts makes I-CAED in water a highly effective tool for the Advanced Oxidation Process, particularly in water disinfection. Experimentally demonstrated Electric Energy per Order value for disinfection of E. coli-contaminated water is as low as 0.135 ± 0.035 kWh/m 3 /order. Estimates show that the implementation of “dry electrodes” configuration reduces the erosion rate of the electrode material by at least one order of magnitude. Spectral analysis reveals that the continuum emission generated by I-CAED in proximity to metal electrodes deviates from the spectra of discharges spatially decoupled from the electrodes. We assume that this spectral divergence is attributable to blackbody-like emission originating from metallic nanoparticles form during the electrode's erosion process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Plasma dynamics, instabilities and OH generation in a pulsed atmospheric pressure plasma with liquid cathode: a diagnostic study

Abstract While plasma–liquid interactions have been an important focus in the plasma research community, the impact of the strong coupling between plasma and liquid on plasma properties and processes remains not fully understood. In this work, we report on the impact of the applied voltage, pulse width and liquid conductivity on the plasma morphology and the OH generation for a positive pulsed DC atmospheric pressure plasma jet with He–0.1% H 2 O mixture interacting with a liquid cathode. We adopted diagnostic techniques of fast imaging, 2D laser induced fluorescence of OH and Thomson scattering spectroscopy. We show that plasma instabilities and enhanced evaporation occur and have a significant impact on the OH generation. At elevated plasma energies, it is found that the plasma contracts due to a thermal instability through Ohmic heating and the contraction coincides with a depletion in the OH density in the core due to electron impact dissociation. For lower plasma energies, the instability is suppressed/delayed by the equivalent series resistor of the liquid electrode. An estimation of the energy flux from the plasma to the liquid shows that the energy flux of the ions released into the liquid by positive ion hydration is dominant, and significantly larger than the energy needed to evaporate sufficient amount of water to account for the measured H 2 O concentration increase near the plasma–liquid interface.

Physics↗
DOE OSTI2026

Machine Learning Enabled Position Detection for 6.78 MHz UAV Wireless Power Transfer System

This paper presents a novel supervised machine learning (SML) approach for accurate position detection of the receiver coil in wireless power transfer (WPT) systems using only secondary-side electrical measurements, with applications in autonomous unmanned aerial vehicle (UAV) charging. The proposed method trains a supervised learning model to map measured secondary-side voltage and current features to the receiver’s spatial position with high precision. This enables an autonomous UAV to determine its location relative to the primary coil center, the optimal position for maximizing wireless charging efficiency. The sensing method is fully integrated into a standard WPT system, utilizing the same primary and secondary coils for both power transfer and position detection, thereby eliminating additional sensing hardware. The use of a 6.78 MHz operating frequency enhances positional sensitivity, as high-frequency near-field electromagnetic fields respond strongly to small spatial variations. Experimental validation is performed on a 30 W scaled prototype featuring a 210 mm × 140 mm primary coil, a 50 mm × 80 mm receiver coil, and a 15 mm air gap. Results demonstrate reliable position estimation and a strong correlation between predicted position and optimal coil alignment. This integrated framework unifying position detection and wireless charging offers a promising foundation for future autonomous electric vertical takeoff and landing (eVTOL) systems, enabling compact, hardware-efficient, and high-accuracy charging solutions.

Colak, Kerim [New York University]↗
DOE OSTI2022

Sustainable bioleaching of lithium-ion batteries for critical materials recovery

The demand for lithium-ion batteries (LIBs) has increased substantially over the last few decades due to their longer lifetime, greater resistance to self-discharge, and higher output voltage compared to other battery types. With the global trend of electrifying vehicle fleets, the number of LIBs reaching their end-of-life (EOL) is expected to grow substantially in the next decade. These EOL LIBs represent a significant secondary source of materials (e.g., Li, Co, Ni, Mn) that can be recovered and reused in LIBs or other products. In this study, we developed a bioleaching process that could recover critical materials from EOL LIBs in an economical and environmentally sustainable manner under industrially relevant conditions. Black mass, i.e., cathode-containing powder, prepared from EOL LIBs was leached using a biolixiviant produced from corn stover by Gluconobacter oxydans bacteria. Iron(II) was used as a reducing agent to promote metal dissolution. Techno-economic analysis (TEA) estimated a potential average profit margin of 21% for processing 10,000 t of black mass per year, which represents approximately 30% of the available black mass in the US in 2020. Life cycle assessment (LCA) demonstrated that bioleaching of spent LIBs could be more environmentally sustainable than alternative hydrometallurgical recovery methods such as hydrochloric acid leaching (16-19 kg vs. 43-91 kg CO 2 equivalent global warming potential per kg of recovered cobalt). The TEA results are highly dependent on the cost of black mass production, which varies by EOL LIB collection and transportation costs. Finally, emerging technologies for deactivating used LIBs for fire safety at collection centers will allow the transport of EOL LIBs as non-hazardous materials, lower the cost of preparing black mass and thereby increase economic prospects for EOL LIBs recycling using this approach.

25 ENERGY STORAGE↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Enabling thermal efficiency improvement and waste heat recovery using liquid air harnessed from offshore renewable energy sources

A novel approach using decoupled processes to harness offshore renewable energy, from marine hydrokinetics, ocean waves, wind, and solar to produce liquid air, is presented here. Offshore renewables interconnection using submarine medium- and high-voltage direct current technologies are used to produce liquid air that can be transported to end-use locations using repurposed liquefied natural gas tankers. Two important possibilities arise from using the proposed technology. The first possibility allows the integration with conventional thermal cycles to improve efficiency. This approach can be used to leverage efficiencies of thermal systems that have already reached a plateau in the maximum achievable efficiency via design and operation optimization. The second possibility is related to the incorporation of low temperature cycles to recover waste heat from other thermal processes. This is important considering that waste heat accounts for more than 60% of the consumed energy in the United States. A detailed technical description of the complete cycle from cryogen generation to end-use of energy is provided. Estimation of efficiency enhancement for thermal plants using liquid air including waste heat recovery is presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗