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At least 37 records · Page 2

VARS Framework

The Verification and Validation Assuring Reliability and Security (VARS) project team has developed the proof-of-concept VARS framework which will be implemented in the form of a software tool called Risk-Informed Verification and Validation Recommendation (RIVVR). The framework will provide Energy Delivery System (EDS) stakeholders with cybersecurity focused verification and validation (V&V) approach which includes list of potentially relevant vulnerabilities to test or address, pre-procurement guidance, and separate lists of relevant standards, tools, and techniques (ST2) to be considered by utilities and vendors

Pal, Seemita↗

AmeriFlux FLUXNET-1F US-Var Vaira Ranch- Ione

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-Var Vaira Ranch- Ione. This is the FLUXNET version of the carbon flux data for the site US-Var Vaira Ranch- Ione produced by applying the standard ONEFlux (1F) software. Site Description - Located in the lower foothills of the Sierra Nevada Mountains on privately owned land, the Vaira Ranch site is classified as a grassland dominated by C3 annual grasses. Managed by local rancher, Fran Vaira, brush has been periodically removed for cattle grazing. Species include a variety of grasses and herbs, including purple false brome, smooth cat's ear, and rose clover. Growing season is confined to the wet season only, typically from October to early May.

Ma, Siyan↗

The Global Modeling and Assimilation Office (GMAO) 4d-Var and its Adjoint-based Tools

The fifth generation of the Goddard Earth Observing System (GEOS-5) Data Assimilation System (DAS) is a 3d-var system that uses the Grid-point Statistical Interpolation (GSI) system developed in collaboration with NCEP, and a general circulation model developed at Goddard, that includes the finite-volume hydrodynamics of GEOS-4 wrapped in the Earth System Modeling Framework and physical packages tuned to provide a reliable hydrological cycle for the integration of the Modern Era Retrospective-analysis for Research and Applications (MERRA). This MERRA system is essentially complete and the next generation GEOS is under intense development. A prototype next generation system is now complete and has been producing preliminary results. This prototype system replaces the GSI-based Incremental Analysis Update procedure with a GSI-based 4d-var which uses the adjoint of the finite-volume hydrodynamics of GEOS-4 together with a vertical diffusing scheme for simplified physics. As part of this development we have kept the GEOS-5 IAU procedure as an option and have added the capability to experiment with a First Guess at the Appropriate Time (FGAT) procedure, thus allowing for at least three modes of running the data assimilation experiments. The prototype system is a large extension of GEOS-5 as it also includes various adjoint-based tools, namely, a forecast sensitivity tool, a singular vector tool, and an observation impact tool, that combines the model sensitivity tool with a GSI-based adjoint tool. These features bring the global data assimilation effort at Goddard up to date with technologies used in data assimilation systems at major meteorological centers elsewhere. Various aspects of the next generation GEOS will be discussed during the presentation at the Workshop, and preliminary results will illustrate the discussion.

Todling, Ricardo↗

Deep reinforcement learning assisted co-optimization of Volt-VAR grid service in distribution networks

With the increasing penetration of distributed energy resources in distribution networks, Volt-VAR control and optimization (VVC/VVO) have become very important to ensure an acceptable quality of service to all customers. System operators can rely on slow-responding utility devices, including capacitor banks and on-load tap changing transformers, along with fast-responding battery and photovoltaic (PV) inverters for the VVC/VVO implementation. Because of variations in response time of these two classes of devices, and different control actions (discrete versus continuous), coordinated and optimal scheduling and operation have become of utmost importance. Here, this paper develops a look-ahead deep reinforcement learning (DRL)-based multi-objective VVO technique to improve the voltage profile of active distribution networks, decrease network and inverter power loss, and save the operational cost of the grid. It proposes a deep deterministic policy gradient (DDPG)-based approach to schedule the optimal reactive and/or active power set-points of fast-responding inverters, and a deep Q-network (DQN)-based DRL agent to schedule the discrete decisions variables of slow-responding assets. The reactive power output of PV and battery smart inverters are scheduled at 30-minute intervals and the capacitors’ commitment status is scheduled with several hour intervals. The proposed framework is validated on the modified IEEE 34-bus and 123-bus test cases with embedded PV and PV-plus-storage. To validate the efficacy of the proposed VVO, it is compared with several scenarios, including the base case without VVO, localized droop control of DERs, DDPG-only, and twin delayed DDPG (TD3) agent-based DRL techniques. The results justify the superior performance of the proposed method to improve the voltage profile, reduce network power loss, and minimize the look-ahead grid operational cost while minimizing the undesirable power losses in inverters as a result of power factor adjustments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Volt-Var Curve Reactive Power Control Requirements and Risks for Feeders with Distributed Roof-Top Photovoltaic Systems

The benefits and risks associated with Volt-Var Curve (VVC) control for management of voltages in electric feeders with distributed, roof-top photovoltaic (PV) can be defined using a stochastic hosting capacity analysis methodology. Although past work showed that a PV inverter’s reactive power can improve grid voltages for large PV installations, this study adds to the past research by evaluating the control method’s impact (both good and bad) when deployed throughout the feeder within small, distributed PV systems. The stochastic hosting capacity simulation effort iterated through hundreds of load and PV generation scenarios and various control types. The simulations also tested the impact of VVCs with tampered settings to understand the potential risks associated with a cyber-attack on all of the PV inverters scattered throughout a feeder. The simulation effort found that the VVC can have an insignificant role in managing the voltage when deployed in distributed roof-top PV inverters. This type of integration strategy will result in little to no harm when subjected to a successful cyber-attack that alters the VVC settings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Examination of B. subtilis var. niger Spore Killing by Dry Heat Methods

Dry heat microbial reduction is the only NASA approved sterilization method to reduce the microbial bioburden on space-flight hardware prior to launch. Reduction of the microbial bioburden on spacecraft is necessary to meet planetary protection requirements specific for the mission. Microbial bioburden reduction also occurs if a spacecraft enters a planetary atmosphere (e.g., Mars) and is heated due to frictional forces. Temperatures reached during atmospheric entry events (>200 C) are sufficient to damage or destroy flight hardware and also kill microbial spores that reside on the in-bound spacecraft. The goal of this research is to determine the survival rates of bacterial spores when they are subjected to conditions similar to those the spacecraft would encounter (i.e., temperature, pressure, etc.). B. subtilis var. niger spore coupons were exposed to a range of temperatures from 125 C to 200 C in a vacuum oven (at <1 Torr). After the exposures, the spores were removed by sonication, dilutions were made, and the spores were plated using the pour plate method with tryptic soy agar. After 3 days incubation at 32 C, the number of colony-forming units was counted. Lethality rate constants and D-values were calculated at each temperature. The calculated D-values were: 27 minutes (at 125 C), 13 minutes (at 135 C), and <0.1 minutes (at 150 C). The 125 C and 135 C survivor curves appeared as concavedownward curves. The 150 C survivor curve appeared as a straight-line. Due to the prolonged ramp-up time to the exposure conditions, spore killing during the ramp-up resulted in insufficient data to draw curves for exposures at 160 C, 175 C, and 200 C. Exploratory experiments using novel techniques, with short ramp times, for performing high temperature exposures were also examined. Several of these techniques, such as vacuum furnaces, thermal spore exposure vessels, and laser heating of the coupons, will be discussed.

bacillus subtilis var niger↗

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗

Quantum Reinforcement Learning for Volt-VAR Control in Power Distribution Systems

Volt-VAR control (VVC) is crucial in active distribution networks for optimizing voltage profiles and minimizing network losses. While traditional deep reinforcement learning (DRL) algorithms exhibit promise for VVC, they often require extensive computational resources to handle such a high-dimensional problem. As a potential solution, quantum reinforcement learning (QRL) algorithms integrate the computational capabilities of quantum computing into the DRL framework. However, existing QRL algorithms struggle with complex VVC problems due to the limitations of current quantum hardware. To bridge this gap, this paper proposes an innovative QRL algorithm featuring an end-to-end architecture that integrates a classical autoencoder, variational quantum circuits (VQCs), and classical post-processing layers. This design efficiently compresses high-dimensional grid states, enabling VQCs to leverage quantum advantages while producing multiple control device outputs tailored for VVC tasks. Numerical studies on three representative distribution systems verify the effectiveness and scalability of the proposed QRL algorithm, and demonstrate its enhanced performance over classical approaches with only approximately 1% of the parameters. Additionally, the robustness of our developed algorithm is validated through noisy quantum environments.

97 MATHEMATICS AND COMPUTING↗

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗

The Challenges of Modeling Distributed Energy Resources (DERs) as Blackstart Resources and for Volt-VAR Optimality

Modeling, testing and instituting Distributed Energy Resources (DERs) as Blackstart Resoucrces presents several challenges due to the fundamental differences between traditional black start resources (e.g., large generators) versus DERs like solar PV systems with battery storage. This paper addresses some of these key challenges. These include intermittency of coordinating DERs to provide continuous power during a black start event, especially during extended periods of cloud cover or when battery energy storage is depleted. This paper additionally addresses the collapsing voltage and stability control challenges specific to maintaining bulk power system stability during black start synchronization These physical and engineering limitations require careful engineering design, modeling and engineering to ensure that DERs can support critical loads and substations during black start events. A variety of additional challenges also exist. Additionally, there are challenges associated with feeder location and low voltage secondary system impacts on DER functions and settings. We compare typical functions and settings for DERs for power factor control and correction. We also demonstrate how voltag control via Volta-VAR power factor correction can be done

Mukherjee, Srijib↗

Distributionally Robust Decentralized Volt-Var Control With Network Reconfiguration

Here, this paper presents a decentralized volt-var optimization (VVO) and network reconfiguration strategy to address the challenges arising from the growing integration of distributed energy resources, particularly photovoltaic (PV) generation units, in active distribution networks. To reconcile control measures with different time resolutions and empower local control centers to handle intermittency locally, the proposed approach leverages a two-stage distributionally robust optimization; decisions on slow-responding control measures and set points that link neighboring subnetworks are made in advance while considering all plausible distributions of uncertain PV outputs. We present a decomposition algorithm with an acceleration scheme for solving the proposed model. Numerical experiments on the IEEE 123 bus distribution system are given to demonstrate its outstanding out-of-sample performance and computational efficiency, which suggests that the proposed method can effectively localize uncertainty via risk-informed proactive timely decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

EB Vs PAM Vs VAR for Uranium Alloys

Questions were raised during the February ’97 PDP Meeting at LLNL as to the advisability of funding three separate melting development programs (Advanced Vacuum Arc Remelt (VAR), Plasma Arc Melting (PAM) and Electron Beam Melting (EB)) through PDP in this era of shrinking research funds. The main issues seemed to be: 1) Have we evaluated the potentials of the three processes sufficiently to eliminate any of them out of hand and 2) Have any of these processes to date produced results which show clear advantages over the other two. The feeling at the meeting toward the latter seemed to be that all three processes required further development before they would be accepted by the complex as the standard. As far as evaluating potential for process improvements, however, we at Livermore did go through somewhat of a trade study in 1993 when we proposed the EB route. It seemed to us that even with the elimination of the skull caster via a VIM/VAR/VAR route, the problem of recycle limitations in the VIM step due to excessive carbon pick-up limited the potential for a great improvement in material utilization using this method. A single-step, cold hearth route looked to be the preferable choice. Both EB and PAM are used commercially as cold hearth processes, and both have been used for the production of refractory and specialty metals; EB since the mid 1950’s and PAM since the mid 1980’s. Both seem to have found their individual niches with some applications being suited to EB and others to PAM. Both can be adapted to continuous casting techniques and both are capable of imparting the high heat fluxes necessary to melt refractory metals. The major differences appear to be that for most applications, the EB process is capable of producing a purer product, while PAM results in less loss of volatile components. There exists an abundance of information in the open literature on the results of processing via both routes on various materials. The attached 1984 paper gives a good explanation of electron beam melting and plasma melting, and, I believe, a fair assessment of the advantages and limitations of both processes.

36 MATERIALS SCIENCE↗

Genome-Wide Study of Hsp90 Gene Family in Cabbage (Brassica oleracea var. capitata L.) and Their Imperative Roles in Response to Cold Stress

Heat shock protein 90 (Hsp90) plays an important role in plant developmental regulation and defensive reactions. Several plant species have been examined for the Hsp90 family gene. However, the Hsp90 gene family in cabbage has not been well investigated to date. In this study, we have been discovered 12 BoHsp90 genes in cabbage ( Brassica oleracea var. capitata L.). These B. oleracea Hsp90 genes were classified into five groups based on phylogenetic analysis. Among the five groups, group one contains five Hsp90 genes, including BoHsp90-1 , BoHsp90-2 , BoHsp90-6 , BoHsp90-10 , and BoHsp90-12 . Group two contains three Hsp90 genes, including BoHsp90-3 , BoHsp90-4 , and BoHsp90 . Group three only includes one Hsp90 gene, including BoHsp90-9 . Group four were consisting of three Hsp90 genes including BoHsp90-5 , BoHsp90-7 , and BoHsp90-8 , and there is no Hsp90 gene from B. oleracea in the fifth group. Synteny analysis showed that a total of 12 BoHsp90 genes have a collinearity relationship with 5 Arabidopsis genes and 10 Brassica rapa genes. The promoter evaluation revealed that the promoters of B. oleracea Hsp90 genes included environmental stress-related and hormone-responsive cis-elements . RNA-seq data analysis indicates that tissue-specific expression of BoHsp90-9 and BoHsp90-5 were highly expressed in stems, leaves, silique, and flowers. Furthermore, the expression pattern of B. oleracea BoHsp90 exhibited that BoHsp90-2, BoHsp90-3, BoHsp90-7, BoHsp90-9, BoHsp90-10, and BoHsp90-11 were induced under cold stress, which indicates these Hsp90 genes perform a vital role in cold acclimation and supports in the continual of normal growth and development process. The cabbage Hsp90 gene family was found to be differentially expressed in response to cold stress, suggesting that these genes play an important role in cabbage growth and development under cold conditions.

Sajad, Shoukat↗

Dry-heat Resistance of Bacillus Subtilis Var. Niger Spores on Mated Surfaces

Bacillus subtilis var. niger spores were placed on the surfaces of test coupons manufactured from typical spacecraft materials including stainless steel, magnesium, titanium, and aluminum. These coupons were then juxtaposed at the inoculated surfaces and subjected to test pressures of 0, 1000, 5000, and 10,000 psi. Tests were conducted in ambient, nitrogen, and helium atmospheres. While under the test pressure condition, the spores were exposed to 125 C for intervals of 5, 10, 20, 50, or 80 min. Survivor data were subjected to a linear regression analysis that calculated decimal reduction times.

Simko, G. J.↗

A mechanical property and stress corrosion evaluation of VIM-ESR-VAR work strengthened and direct double aged Inconel 718 bar material

Presented are the mechanical properties and the stress corrosion resistance of triple melted vacuum induction melted (VIM), electro-slag remelted (ESR), and vacuum arc remelted (VAR), solution treated, work strengthened and direct double aged Inconel 718 alloy bars 4.00 in. (10.16) and 5.75 in. (14.60 cm) diameter. Tensile, charpy v-notched impact, and compact tension specimens were tested at ambient temperature in both the longitudinal and transverse directions. Longitudinal tensile and yield strengths in excess of 220 ksi (1516.85 MPa) and 200 ksi (1378.00 MPa) respectively, were realized at ambient temperature. Additional charpy impact and compact tension tests were performed at -100 F (-73 C). Longitudinal charpy impact strength equalled or exceeded 12.0 ft-lbs (16.3 Joules) at ambient and at -100 F(-73 C) while longitudinal compact (LC) tension fracture toughness strength remained above 79 ksi (86.80 MPa) at ambient and at -100 F(-73 C) temperatures. No failures occurred in the longitudinal or transverse tensile specimens stressed to 75 and 100 percent of their respective yield strengths and exposed to a salt fog environment for 180 days. Tensile tests performed after the stress corrosion test indicated no mechanical property degradation.

Montano, J. W.↗

A preliminary mechanical property and stress corrosion evaluation of VIM-VAR work strengthened and direct aged Inconel 718 bar material

This report presents a preliminary mechanical property and stress corrosion evaluation of double melted (vacuum induction melted (VIM), and vacuum arc remelted (VAR)), solution treated, work strengthened and direct aged Inconel 718 alloy bar (5.50 in. (13.97 cm) diameter). Two sets of tensile specimens, one direct single aged and the other direct double aged, were tested at ambient temperature in both the longitudinal and transverse directions. Longitudinal tensile and yield strengths in excess of 200 ksi (1378.96 MPa) and 168 ksi (1158.33 MPa), respectively, were realized at ambient temperature, for the direct double aged specimen. No failures occurred in the single or double edged longitudinal and transverse tensile specimens stressed to 75 and 100 percent of their respective yield strengths and exposed to a salt fog environment for 180 days. Tensile tests performed after the stress corrosion test showed no mechanical property degradation.

Montano, J. W.↗