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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Can artificial intelligence and data-driven machine learning models match or even replace process-driven hydrologic models for streamflow simulation?: A case study of four watersheds with different hydro-climatic regions across the CONUS

With recent developments in computational techniques, Data-driven Machine Learning Models (DMLs) have shown great potential in simulating streamflow and capturing the rainfall-runoff relationship in given watersheds, which are traditionally fulfilled by Process-based Hydrologic Models (PHMs). There are debates on whether the DMLs can outperform and possibly replace the classical PHMs for streamflow simulation and river forecasting, but no clear conclusions have been made. This study aims to investigate whether the newer DMLs have any potential in further improving the simulation accuracy of classical PHMs, and vice versa. To do this, we compared a few popular PHMs and DMLs over four watersheds across the Continental US (CONUS) that are associated with different input, climate, and regional conditions. A total of five hydrologic models were chosen, including (1) two classical lumped models, i.e., the Sacramento Soil Moisture Accounting (SAC-SMA) and Xinanjiang (XAJ); (2) one modern distributed model, termed Coupled Routing and Excess Storage (CREST); (3) and two DMLs including an Artificial Neural Networks (ANN) and a deep learning model, termed Long Short Term Memory (LSTM). Our results demonstrated that the DMLs still significantly biased when using the baseline input scenario with the PHMs. However, the DMLs fed with delayed input scenarios had great potential and can reach high simulation accuracy. The DMLs, especially the ANN, outperformed other employed models under the rainfall-runoff relationship in which rainfall dominantly drives. Furthermore, the DMLs also showed better performance in the high-flow regime, while the PHMs had a better performance for the low-flow regime, implying both PHMs and DMLs have their own merits and are worthy of joint development. In general, our study indicated a great potential of using DMLs to simulate streamflow, but further studies are still needed to verify the transferability and scalability of DMLs in large-scale experiments, such as the Distributed Model Intercomparison Projects 1&2 conducted by National Weather Services but to compare modern DMLs and PHMs.

58 GEOSCIENCES↗
DOE OSTI2024

Identifying multiple synergistic factors on the susceptibility to stress relaxation cracking in variously heat-treated weldments

The 347H austenitic stainless steel has been widely used for pressure vessels and pipeline (PVP) applications due to its excellent creep and corrosion resistance, which fit ideally to the harsh conditions in petrochemical industries, fossil fuel or nuclear power plants, and modern energy storages. However, a failure mode has been commonly observed with cracks emerging at the heat affected zone (HAZ) of weldments during post-weld heat treatment (PWHT) or under intermediate to high temperature service conditions. This phenomenon is termed as Stress Relaxation Cracking (SRC) since the purpose of PWHT is to relieve the welding-induced residual stress fields, or as Stress Age Cracking (SAC) if failure happens during service. A leading literature explanation of this failure suggests that the residual stress relaxation and the precipitation dissolution and/or re-precipitation occur in the same temperature range, which can lead to locally high strains and thus to crack at the grain boundaries. Since in situ spatial measurements of residual stress fields, microstructural evolution, and failure processes are nearly infeasible, this work recourses to a micromechanical finite element framework that models the high temperature failure as the nucleation and growth of grain boundary cavities, whereas various parameters such as thermomechanical loading history and its evolution, the competition of grain-interior dislocation creep and grain-boundary diffusion in failure lifetime, and microstructural heterogeneities (such as the precipitate free zone near grain boundaries) can be quantitatively incorporated. It can be concluded from these microstructure-explicit simulations that an accurate knowledge of residual stress evolution and a carefully calibrated set of material constitutive parameters are the essential prerequisites for lifetime predictions. The understanding of individual governing factors also leads to a mechanistic interpretation of the observed SRC susceptibility C-curves. In conclusion, these results suggest that the criticality of residual stress evolution, but not the precipitation-induced local strains, be the leading factor for SRC.

347H stainless steel weldments↗
DOE OSTI2022

Single-Atom Pt Boosting Electrochemical Nonenzymatic Glucose Sensing on Ni(OH) 2 /N-Doped Graphene

Conventional nanomaterials in electrochemical non-enzymatic sensing face huge challenge due to their complex size-, surface- and composition- dependent catalytic properties and low active site density. In this work, we designed a single-atom Pt supported on Ni(OH) 2 nanoplates/nitrogen-doped graphene (Pt 1 /Ni(OH) 2 /NG) as the first example for constructing a single-atom catalyst based electrochemical non-enzymatic glucose sensor. The resulting Pt 1 /Ni(OH) 2 /NG exhibited a low anode peak potential of 0.48 V and high sensitivity of 220.75 μA mM -1 cm -2 towards glucose, which are 45 mV lower and 12 times higher than those of Ni(OH) 2 , respectively. The catalyst also showed excellent selectivity for several important interferences, short response time of 4.6 s, and high stability over 4 weeks. Experimental and density functional theory (DFT) calculated results reveal that the improved performance of Pt 1 /Ni(OH) 2 /NG could be attributed to stronger binding strength of glucose on single-atom Pt active centers and their surrounding Ni atoms, combined with fast electron transfer ability by the adding of the highly conductive NG. Finally, this research sheds light on the applications of SACs in the field of electrochemical non-enzymatic sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

High-Loading Single-Atom Catalyst via On-Surface Synthesis of a Metal-Covalent Organic Framework for Oxygen Reduction Reaction

The development of active catalysts with both high metal efficiency and use of earth abundant metals is the ultimate goal for advancing the required commercially viable and sustainable energy conversion technologies of the future. Metal-organic frameworks (MOFs) have emerged as promising candidates due to their high surface area and tunable active sites. Here, this study aims to fabricate a new type of high metal loading single-atom catalysts (SACs) based on 2D metal-organic covalent organic frameworks (MCOFs) with uniform, active and stable Fe-N 3 sites. The MCOFs were synthesized through an on-surface polymerization process using Fe and melamine as precursors. The polymerization steps were characterized using operando high-pressure scanning tunneling microscopy (HP-STM), in situ X-ray photoelectron spectroscopy (XPS), low-temperature STM (LT-STM), and computational calculations. The synthesized MCOFs demonstrated favorable adsorption and activation of O 2 at the Fe-N 3 sites, and it is predicted to be active for the oxygen reduction reaction (ORR). The surface chemistry and functionality of 2D MCOFs can be rationally designed by varying the metal atoms and organic linkers, offering a versatile platform for diverse applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Recent Improvements to the NWChem COSMO Module

This work presents recent developments in the COSMO solvation model implementation in NWChem. A new cavity construction approach, based on the solvent-excluding surface (SES) and utilizing the well-established GEPOL algorithm, has been introduced. Additionally, a straightforward procedure to merge surface segments that are too close─often a source of numerical artifacts─has been implemented. The available methods for correcting outlying surface charges have also been reviewed and improved. To validate the new implementation, we computed dielectric solvation energies for a chemically diverse set of approximately 100 molecules, including neutral species, small ions, and common ionic liquid components. Results were compared to those from GAMESS using the double-cavity method as a reference. Although the double-cavity approach can be regarded as more accurate, the simpler correction schemes available in NWChem─based on scaling factors or Lagrange multipliers─can achieve excellent agreement if the potential is also properly corrected, with mean unsigned deviations of around 0.15 kcal/mol. Predictions of typical vapor–liquid and liquid–liquid equilibria using a COSMO-SAC variant based on NWChem also showed very promising results.

Cavities↗
DOE OSTI2021

Catalytic CO Oxidation on MgAl 2 O 4 -Supported Iridium Single Atoms: Ligand Configuration and Site Geometry

Probing and understanding the local chemical environment of an active site is essential for designing high-performance single-atom catalysts (SACs). Density functional theory (DFT) calculations were performed to investigate the ligand configuration and site geometry of MgAl 2 O 4 -supported iridium single atoms (Ir-1) toward catalytic carbon monoxide (CO) oxidation. We employed MgAl 2 O 4 (111) and MgAl 2 O 4 (211) as the model substrates with adsorbed Ir single atoms of different site geometries. DFT calculations revealed that the Mg-site on MgAl 2 O 4 (111) and the step site on MgAl 2 O 4 (211) are the most stable adsorption sites for Ir single atoms. Irrespective of site choices, CO oxidation on supported Ir single atoms follows the Eley-Rideal (E-R) mechanism, in which the surface oxygen vacancies close to the Ir single atoms activate molecular O 2 with a negligible barrier and the rate-limiting step is the gas-phase CO directly attacking the O-Ir species that is modulated by a CO ligand. Furthermore, first-principles X-ray absorption near-edge spectra of reaction intermediates along with in situ/operando X-ray absorption spectroscopy (XAS) suggest that Ir single atoms adsorb primarily on the step sites of MgAl 2 O 4 . However, microkinetic modeling predicts that a higher activity can be attained on the equally stable Mg-site, maximizing the population of which in catalyst synthesis might prove fruitful in future studies. Electronic structure analysis indicates that the CO ligand increases the reactivity of adsorbed oxygen atoms bound to Ir single atoms by increasing the antibonding nature of the O-Ir bond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Finite-Temperature Structures of Supported Subnanometer Catalysts Inferred via Statistical Learning and Genetic Algorithm-Based Optimization

Single-atom catalysts (SACs) minimize noble metal utilization and can alter the activity and selectivity of supported metal nanoparticles. However, the morphology of active centers, including single atoms and subnanometer clusters of a few atoms, remains elusive due to experimental challenges. The computational cost to describe numerous cluster shapes and sizes makes direct first-principles calculations impractical. We present a computational framework to enable structure determination for single-atom and subnanometer cluster catalysts. As a case study, we obtained the low energy structures of Pd n (n = 1-21) clusters supported on CeO 2 (111), which are critical components of automobile three-way catalysts. Trained on density functional theory data, a three-dimensional cluster expansion is established using statistical learning to describe the Hamiltonian and predict energies of supported Pdn clusters of any structure. Low energy stable and metastable structures are identified using a Metropolis Monte Carlo-based genetic algorithm in the canonical ensemble at 300 K. We observe that supported single atoms sinter to form bilayer clusters and large cluster isomers share similarities in both shape and energy, and elucidate the significance of the support and microstructure on cluster stability. We discovered a simple surrogate structure-energy model, where the energy per atom scales with the square root of the average first coordination number, which can be used to estimate energies and compare the stability of clusters. Our framework, applicable to any metal/support system, fills an important methodological gap to predict the stability of supported metal catalysts in the subnanometer regime.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Nitrogenated Graphene Quantum Dot-Derived Copper Single-Atom Catalyst for Oxygen Reduction Reaction

Despite the promise of fuel cells as sustainable energy conversion technologies, their widespread adoption is hindered by the high cost of platinum group metal (PGM) catalysts, particularly for catalyzing the oxygen reduction reaction (ORR) at the cathode. Here, we report copper-based single-atom catalysts (Cu-SACs) as cost-effective non-PGM alternatives for ORR. The catalysts were synthesized via simple pyrolysis of pyrene-derived amine-terminated graphene quantum dots (GQDs) in the presence of nitrogen and metal precursors. The abundant nitrogen functionality in GQDs effectively stabilized isolated Cu atoms during their conversion to porous carbon. A subsequent acid-washing step yielded a high density of atomically dispersed Cu active sites. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and high-resolution scanning transmission electron microscopy (HR-STEM) confirmed the effective incorporation of isolated Cu atoms into the carbon matrix through copper–nitrogen (Cu-N) coordination. Electrochemical measurements revealed excellent ORR activity with a dominant four-electron pathway. This synthetic strategy provides a practical route to developing economically viable, non-precious metal catalysts.

catalysts↗
DOE OSTI2026

Single-Atom Nickel Dispersed on Mo 2 TiC 2 T x MXene for Upcycling of Polyolefins via Catalytic Hydropyrolysis for Fuels and Lubricants

Plastic waste has been a major social and environmental problem. Chemical upcycling of plastic waste into transportation fuels or lubricant oil has emerged as an attractive and promising approach to convert plastic waste into valuable products. However, conventional catalyst systems often require high-pressure hydrogen, prolonged residence time, and the use of noble metal catalysts. Here, we present zero-valent nickel single atoms on Mo-based MXenes (Ni/Mo 2 TiC 2 T x ) for effective hydrogenation of polyolefins. In situ spectroscopic and microscopic characterizations demonstrate the formation of Ni–Mo and Ni–C bonds at a low Ni loading, resulting in the formation of dispersed intercalated Ni atoms. The catalysts were then employed to convert polyethylene into fuels and lubricant molecules under atmospheric hydrogen pressure, short vapor residence time (τ < 1 s), and mild reaction temperature (300 °C). We further demonstrated the possibility of tuning the Ni structure by changing the Ni loading, attributed to the strong metal–support interactions (MSIs) with the Mo 2 TiC 2 T x support. Under optimized conditions, 22.5 C% gasoline, 12.0 C% diesel, 19.2 C% jet fuel (JP-8), and 37.4 C% lubricant were produced over 0.5% Ni/Mo 2 TiC 2 T x . This work highlights the potential of utilizing MSIs of Mo 2 TiC 2 T x MXenes to synthesize single-atom catalysts (SACs) for upcycling plastic waste into higher-value products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Mechanistic insight into the active centers of single/dual-atom Ni/Fe-based oxygen electrocatalysts

Single-atom catalysts with maximum metal utilization efficiency show great potential for sustainable catalytic applications and fundamental mechanistic studies. We here provide a convenient molecular tailoring strategy based on graphitic carbon nitride as support for the rational design of single-site and dual-site single-atom catalysts. Catalysts with single Fe sites exhibit impressive oxygen reduction reaction activity with a half-wave potential of 0.89 V vs. RHE. We find that the single Ni sites are favorable to promote the key structural reconstruction into bridging Ni-O-Fe bonds in dual-site NiFe SAC. Meanwhile, the newly formed Ni-O-Fe bonds create spin channels for electron transfer, resulting in a significant improvement of the oxygen evolution reaction activity with an overpotential of 270 mV at 10 mA cm –2 . We further reveal that the water oxidation reaction follows a dual-site pathway through the deprotonation of *OH at both Ni and Fe sites, leading to the formation of bridging O 2 atop the Ni-O-Fe sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Author Correction: Genome-guided isolation of the hyperthermophilic aerobe Fervidibacter sacchari reveals conserved polysaccharide metabolism in the Armatimonadota

Correction to: Nature Communicationshttps://doi.org/10.1038/s41467-024-53784-3, published online 4 November 2024 In the version of this article initially published, Table 1 did not include the properties of the taxa being proposed or refer directly to another location in the main manuscript describing the properties. As such, the original manuscript did not comply with Rule 27 (2)(c) of the ICNP. Also, Table 1 listed the order Fervidibacterales as the nomenclatural type for the class Fervidibacteria, which violates latest emended version of Rule 15 stating that the nomenclatural type for a class must be a genus. Below we provide a modification of Table 1 containing protologues with these errors corrected. We have also changed the order of the taxa in the table to meet the most common ordering. (Table presented.) Taxon names proposed under the ICNP Proposed taxon Etymology Description Genus Fervidibacter Fer.vi.di.bac’ter. L. masc. adj. fervidus, hot, steaming; N.L. masc. n. bacter, a rod; N.L. masc. n. Fervidibacter, a hot rod Thermophilic or hyperthermophilic inhabitants of freshwater thermal environments. All members are likely polysaccharide-degrading chemoheterotrophs with numerous carbohydrate-active enzymes encoded in their genomes. Aerobic, with high-affinity and/or low-affinity terminal oxidases present in the genomes. The oxidative pentose phosphate pathway and the tricarboxylic acid cycle are complete in genomes belonging to the genus. Gram-stain-negative and diderm cell envelope structure. Ovoid- to rod-shaped morphology. Spores are not formed. The genus is a distinct phylogenetic lineage in the family Fervidibacteraceae, the order Fervidibacterales, and the class Fervidibacteria in the phylum Armatimonadota. The type species is Fervidibacter sacchariT. Species Fervidibacter sacchari sac’cha.ri. N.L. gen. n. sacchari, of sugar Hyperthermophilic, microaerophilic, facultatively anaerobic, and grows chemoheterotrophically on monosaccharides and polysaccharides. Cells are ovoid- to rod-shaped, Gram-stain negative, and are 0.9–1.3 µm in width and 1.6–3.6 µm in length. Grows between 65 and 87.5 °C and an optimum temperature of 80 °C, and a pH range of 6.5–8.6 with an optimum pH of 7.5. Grows at an optimum O2 concentration of 5–10%. Grows on D-arabinose, D-galactose, D-glucose, D-rhamnose, D-ribose, D-xylose, chondroitin sulfate, colloidal chitin, galactan, gellan gum, guar gum, karaya gum, locust bean gum, xantham gum, xyloglucan, β-glucan, glycogen, starch, AFEX-pretreated corn stover, miscanthus, sugarcane bagasse, acetate and casamino acids. Grows weakly on xyloglucan under fermentation conditions. The major fatty acids (>10%) are C16:0, C18:0 and/or cyclo-C17:0, and iso-C16:0. The major respiratory quinones (>10%) are MK-8 and MK-9. The isolate and genomes of the species have been recovered from geothermal springs in the Great Basin, Nevada, USA. GC content of genomes range between 51–52%. Subunits for both the high-affinity and low-affinity terminal oxidases are encoded in the genomes. Genomes also encode a Group 3d [NiFe] hydrogenase, which produces hydrogen as an electron sink for NAD+ regeneration. The type strain PD1T (= JCM 39283T = DSM 113467T) was isolated from Great Boiling Spring in Nevada, USA. Family Fervidibacteraceae Fer.vi.di.bac.te.ra’ce.ae. N.L. masc. n. Fervidibacter type genus of the family; L. suff. -aceae ending to denote a family; N.L. fem. pl. n. Fervidibacteraceae the family of the genus Fervidibacter Thermophilic or hyperthermophilic inhabitants of freshwater thermal environments. All members are likely polysaccharide-degrading chemoheterotrophs with numerous carbohydrate-active enzymes encoded in their genomes. Aerobic, with high-affinity and/or low-affinity terminal oxidases present in the genomes. The oxidative pentose phosphate pathway and the tricarboxylic acid cycle are complete in genomes belonging to the family. The family is a distinct phylogenetic lineage in the order Fervidibacterales and the class Fervidibacteria in the phylum Armatimonadota. The type genus is Fervidibacter. Order Fervidibacterales Fer.vi.di.bac.te.ra’les. N.L. masc. n. Fervidibacter type genus of the order; L. suff. -ales ending to denote an order; N.L. fem. pl. n. Fervidibacterales the order of the genus Fervidibacter Thermophilic or hyperthermophilic inhabitants of freshwater thermal environments. All members are likely polysaccharide-degrading chemoheterotrophs with numerous carbohydrate-active enzymes encoded in their genomes. Aerobic or strictly anaerobic. Phylogenomic placement of this lineage within the Fervidibacteria and relative evolutionary divergence supports delineation of this lineage as an order within the class Fervidibacteria and phylum Armatimonadota. The type genus is Fervidibacter. Class Fervidibacteria Fer.vi.di.bac.te’ri.a. N.L. masc. n. Fervidibacter type genus of the type order of the class; L. suff. -ia ending to denote a class; N.L. neut. pl. n. Fervidibacteria the class of the order Fervidibacterales Thermophilic or hyperthermophilic inhabitants of freshwater thermal environments. All members are likely polysaccharide-degrading chemoheterotrophs with numerous carbohydrate-active enzymes encoded in their genomes. Aerobic or strictly anaerobic. Phylogenomic placement of this lineage within the Armatimonadota and relative evolutionary divergence supports delineation of this lineage as a class within the Armatimonadota. The type genus is Fervidibacter. The error has not been corrected in the PDF or HTML versions of the Article.

Nou, Nancy O↗
DOE OSTI2023

Synthesis of core/shell nanocrystals with ordered intermetallic single-atom alloy layers for nitrate electroreduction to ammonia

Structurally ordered intermetallic nanocrystals (NCs) and single-atom catalysts (SACs) are two emerging catalytic motifs for sustainable chemical production and energy conversion. However, both have synthetic limitations which can lead to the aggregation of NCs or metal atoms. Single-atom alloys (SAAs), which contain isolated metal atoms in a host metal, can overcome the aggregation concern because of the thermodynamic stabilization of single atoms on host metal surfaces. We report a direct solution-phase synthesis of Cu/CuAu core/shell NCs with tunable SAA layers. This synthesis can be extended to other Cu/CuM (M = Pt, Pd) systems, in which M atoms are isolated in the copper host. Using this method, the density of SAAs on a copper surface can be controlled, resulting in both low and high densities of single atoms. Alloying gold into the copper matrix introduced ligand effects that optimized the chemisorption of *NO 3 and *N. As a result, the densely packed Cu/CuAu material demonstrated a high selectivity toward NH 3 from the electrocatalytic nitrate reduction reaction with an 85.5% Faradaic efficiency while maintaining a high yield rate of 8.47 mol h -1 g -1 . This work advances the design of atomically precise catalytic sites by creating core/shell NCs with SAA atomic layers, opening an avenue for broad catalytic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Carboxylic acid ligand substituent impacts hydrosilylation activity of platinum single atom catalysts on ceria

Current industrially employed hydrosilylation catalysts rely on homogeneous platinum catalysts which are not recovered after the reaction. To eliminate this issue, our group has been working to optimize recyclability of heterogeneous platinum single atom catalysts (SACs) on ceria via 1,10-phenanthroline-5,6-dione ligands (PDO), which incorporates mono (PDO-C) and dicarboxylic acid (PDO-C2) groups in the 2- and 9-position of PDO ligand to increase metal–surface interaction. DRIFTS results confirm carboxylic acid coordination to the terminal hydroxy groups of the ceria surface. New catalyst synthesis conditions wherein PDO was combined with the metal prior to exposure to the surface allow control of Pt oxidation state on the surface. Here, the highest metal loading was observed for PDO and PDO-C, correlating with improved catalytic recyclability compared to the PDO-C2 ligand. It is proposed that the location of the carboxylic acid groups and the steric effects can explain the lower activity and metal loading for PDO-C2 ligands. Post-reaction XPS and DRIFTS spectra show the appearance of new Si and O species on the catalyst during the hydrosilylation reaction, indicating the silane reagent is depositing on the surface. The silane coverage and leaching of catalyst from the surface is the cause for the reduced catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Hanging droplets from liquid surfaces

Natural and man-made robotic systems use the interfacial tension between two fluids to support dense objects on liquid surfaces. Here, we show that coacervate-encased droplets of an aqueous polymer solution can be hung from the surface of a less dense aqueous polymer solution using surface tension. The forces acting on and the shapes of the hanging droplets can be controlled. Sacs with homogeneous and heterogeneous surfaces are hung from the surface and, by capillary forces, form well-ordered arrays. Locomotion and rotation can be achieved by embedding magnetic microparticles within the assemblies. Direct contact of the droplet with air enables in situ manipulation and compartmentalized cascading chemical reactions with selective transport. Applications including functional microreactors, motors, and biomimetic robots are evident.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Deep Reinforcement Learning for Distribution System Cyber Attack Defense with DERs

The use of smart inverter capabilities of distributed energy resources (DERs) enhances the grid reliability but in the meanwhile exhibits more vulnerabilities to cyber-attacks. This paper proposes a deep reinforcement learning (DRL)-based defense approach. The defense problem is reformulated as a Markov decision making process to control DERs and minimizing load shedding to address the voltage violations caused by cyber-attacks. The original soft actor-critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions for controlling DERs' setpoints and loadshedding scenarios. Numerical comparison results with other control approaches, such as Volt-VAR and Volt-Watt on the modified IEEE 33-node, show that the proposed method can achieve better voltage regulation and have less power losses in the presence of cyber-attacks.

active distribution systems↗
DOE OSTI2022

Deep Reinforcement Learning for Distribution System Restoration Using Distributed Energy Resources and Tie-Switches

Distributed energy resources (DERs), such as solar PVs and energy storage, can be used to restore distribution system critical loads after the extreme weather events to increase grid resilience. However, coordinating multiple DERs together with tie-switches for multi-step restoration process under renewable uncertainty is challenging. This paper proposes a deep reinforcement learning to control discrete actions of switching on/off tie switches and DERs for critical load restoration. The restoration problem is first cast into the Markov decision process suitable for DRL. Then, the original soft actor critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions. Numerical comparison results with other stochastic optimization-based approaches on the modified IEEE 33-bus system show that the proposed method can achieve fast critical load restoration in the presence of substation power outage while maintaining system voltage limit throughout the restoration process.

active distribution systems↗
DOE OSTI2022

Multi-Agent Deep Reinforcement Learning for Realistic Distribution System Voltage Control Using PV Inverters

Over the last few decades, the deployment of distributed solar photovoltaic (PV) systems has increased consistently. High PV penetration could cause adverse effects on the grid, such as voltage violations. This paper proposes a new distributed soft actor-critic based multi-agent deep reinforcement learning (SAC-MADRL) control solution to minimize the PV real power curtailment while keeping the grid voltage in an acceptable range. New reward functions have been designed to coordinate different agents during the learning process, yielding improved convergence. Comparison results with other control methods on a real feeder in western Colorado U.S. with 80% penetration of PVs demonstrate that the proposed method has better capability of effectively regulating voltage while minimizing the PV real power curtailment.

distribution system↗
DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗