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At least 253 records · Page 14

Backup power or bill savings? How electricity tariffs impact residential solar-plus-storage usage in the United States

Adoption of paired solar-plus-storage systems has accelerated in recent years, driven by both the demand for backup power and a desire to manage utility bills. Tradeoffs between those two uses can arise through the reserve setting on the battery storage system, which serves to maintain a minimum state of charge in case of a power interruption. Our paper applies an economic framework to evaluate this tradeoff in terms of changes in bill savings and customer reliability value across reserve levels, considering how those tradeoffs depend on the underlying electricity rate structure and levels. The analysis is based on a representative set of load profiles, solar profiles, tariff designs, and stochastic power interruption events across ten different regions in the United States. We find that the opportunity cost of holding storage capacity in reserve, in terms of foregone bill reductions, outweighs any gains in reliability value from mitigated power interruptions in the majority of customer situations. Higher storage reserve levels increase total customer value only in specific circumstances, such as for customers with inferior reliability (10x average interruptions), with a very high value of lost load ($50/kWh), and with tariff or interconnection rules that disallow grid charging. However, even this result is dampened when considering tariff designs with higher price differentials that increase the opportunity cost of holding storage in reserve (e.g. import/export or time-of-use rates). Allowing grid charging in tariffs essentially eliminates the necessity to hold any storage in reserve in all sensitivity cases explored.

Electric resilience↗

Mitigation of rapid capacity decay in silicon-LiNi 0.6 Mn 0.2 Co 0.2 O 2 full batteries

Silicon (Si)-based materials have been considered as the most promising anode materials for high-energy-density lithium-ion batteries because of their higher storage capacity and similar operating voltage, as compared to the commercial graphite (Gr) anode. But the use of Si anodes including silicon-graphite (Si-Gr) blended anodes often leads to rapid capacity decay in Si-Gr/LiNixMnyCo z O 2 (x+y+z=1) full cells, which has been attributed to surface instability of the Si component. In addition to stabilizing the surface, this work investigates the potential of the Si-Gr blended anodes in a full-cell configuration and its impact on the capacity contribution from active components. Using dQ/dV plots of the full cells, a powerful but simple-to-implement differential potential approach is developed to decouple the capacity contribution and degradation from the graphite and silicon components. Data collected from three-electrode cells confirm the results from the differential potential approach, which suggests a voltage slippage to a higher voltage at the blended anode side. Additionally, the voltage slippage causes a reduced utilization of the Gr component and exacerbates side reactions between the Si-Gr anode and carbonate electrolytes. Furthermore, based on these failure mechanisms, we adopted a mitigation strategy to tune the open circuit voltage of the prelithiated anode while stabilizing the surface. As a result, the full cells with the modified Si-Gr anodes (mass loading, 2.5 mAh/cm 2 ) offer a highly reversible full-cell energy density of 390 Wh/kg (based on the mass of both anode and cathode materials in a full cell) with a cycling CE of 99.9% over 200 cycles.

25 ENERGY STORAGE↗

Efficient I/O for Neural Network Training with Compressed Data

FanStore is a shared object store that enables efficient and scalable neural network training on supercomputers. By providing a global cache layer on node-local burst buffers using a compressed representation, it significantly enhances the processing capability of deep learning (DL) applications on existing hardware. In addition, FanStore allows POSIX-compliant file access to the compressed data in user space. We investigate the tradeoff between runtime overhead and data compression ratio using real-world datasets and applications, and propose a compressor selection algorithm to maximize storage capacity given performance constraints. We consider both asynchronous (i.e., with prefetching) and synchronous I/O strategies, and propose mechanisms for selecting compressors for both approaches. Using FanStore, the same storage hardware can host 2-13x more data for example applications without significant runtime overhead. Empirically, our experiments show that FanStore scales to 512 compute nodes with near linear performance scalability.

Zhang, Zhao↗

NCS design and evaluation of new high-density storage containers

Changes in mission at Y-12 National Security Complex evolving over the past five years have resulted in increased levels of storage utilization. This has prompted a need to reevaluate storage capacity and efficiency. As a result, Y-12 Nuclear Criticality Safety (NCS) and Packaging Engineering developed and designed a new modified neutron absorbing container. The high-density storage container is known as the 12-Place Rackable Can Storage Box (12-Place RCSB) and will allow safe and efficient storage of fissile material at the Highly Enriched Uranium Materials Facility (HEUMF).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Characterization of the Triassic Newark Basin of New York and New Jersey for Geologic Storage of Carbon Dioxide

The project Characterization of the Triassic Newark Basin of New York and New Jersey for Geologic Storage of Carbon Dioxide is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. Sandia Technologies, LLC, and co-investigator Conrad Geoscience Corporation, examined the potential for large-scale, permanent CO2 storage in sedimentary strata within the Newark Rift Basin. The Newark Rift Basin underlies an industrialized, developed region comprising parts of New York, New Jersey, and Pennsylvania. The project characterized and investigated the suitability of Triassic age sedimentary formations for potential geologic CO2 storage. The project team drilled and cored two test wells to define the sedimentary geologic formations underlying the basin and to document or reach basement rock. With this geologic characterization phase, an integration of seismic, geologic, borehole, and formation core results provided a higher resolution assessment of CO2 storage potential. The Stockton Formation is known to be a potentially favorable geologic storage formation in the basin. In 2011, the 1-NYSTA Tandem Lot stratigraphic test well was drilled to a depth of 6,855 feet in the northern portion of the Newark Basin in southern New York State. Approximately 9 miles south-southeast on the Lamont Doherty Campus, TW-4 was drilled and cored in 2013 to a depth of 1,802 feet and contacted apparent igneous basement at a depth of 1,712 feet. Both wells penetrated the Palisades Sill ranging from 800 feet thick in the eastern well to approximately 1,800 feet in thickness at the 1-NYSTA Tandem Lot deep drill site. A diabase sill can provide an excellent seal and dense confining layer for potential CO2 storage reservoirs and flow layers that are situated beneath it within the Stockton Sandstone. The Stockton Sandstone was encountered beneath the sill in the TW-4 well on the Lamont campus, and data integration suggests that it was likely observed near total depth in the deep 1-NYSTA Tandem Lot well. The test wells confirm and define reservoirs are present beneath the sill and offer CO2 storage potential. The integration of geologic and reservoir characterization of well logs, formation cores, and formation fluids indicated Triassic age lacustrine playa lake and mudbank shales of the Upper Passaic Group can provide an effective seal for the porous and permeable underlying sandstone reservoir layers. This project acquired seismic data, drilled borehole well logs, acquired core samples, and integrated these findings to provide a better understanding of the subsurface geologic formations in the Newark Rift Basin. These findings have contributed to a higher degree of accuracy in predicting potential geologic storage opportunities, while refining geologic storage capacity estimates for the indicated reservoirs and flow units.

.las↗

Mass optical storage-tape (MOST)

In today's large mainframe and supercomputer environment there exists a continuous demand for increased performance in digital storage systems. The user need for near-line storage capacity is currently doubling every four years. In addition to higher capacity, a desire exists for higher data transfer rates, and longer term database archivability, at lower, and lower cost. Each component of this quartet of demands appears to be insatiable. Magnetic tape technology presently dominates the digital mass storage markets, but the continuous growth of requirements is drawing attention to the limitations of the technology as an archival mass storage medium. The lowest cost option currently available for long term data storage is to use magnetic tape, although it is not well suited to meeting the need for many tens of years of reliable storage. Today, the majority of magnetic tape mass storage systems are based on the IBM 3480/3490 (or compatible) tape drives. These drives offer only moderate transfer rates and relatively small increments of storage, both of which create a logistics problem due to the large numbers of cartridges necessary in a typical system and the time taken to transfer data. Both higher cartridge capacity and data transfer rates are available in some helical scan magnetic tape systems; however, these command a substantially higher price, exacerbating the cost problem, and are not compatible with most installed systems or tape databases.

Oakley, William S.↗

The effect of 10 at.% Al addition on the hydrogen storage properties of the Ti 0.33 V 0.33 Nb 0.33 multi-principal element alloy

We report here a thorough study on the effect of 10 at.% Al addition into the ternary equimolar Ti 0.33 V 0.33 Nb 0.33 alloy on the hydrogen storage properties. Despite a decrease of the storage capacity by 20%, several other properties are enhanced by the presence of Al. The hydride formation is destabilized in the quaternary alloy as compared to the pristine ternary composition, as also confirmed by machine learning approach. The hydrogen desorption occurs at lower temperature in the Al-containing alloy relative to the initial material. Moreover, the Al presence improves the stability during hydrogen absorption/desorption cycling without significant loss of the capacity and phase segregation. Finally, this study proves that Al addition into multi-principal element alloys is a promising strategy for the design of novel materials for hydrogen storage.

36 MATERIALS SCIENCE↗

Solar Heating System installed at Belz Investment Company, Memphis, Tennessee

A hot air solar system which utilizes flat plate air collectors is discussed. Collector areas for each of four buildings cover 780 sq ft, with storage capacity of 390 cu ft per building. The air system has a special air handling unit to move air through the collectors and into and out of the rock storage, with connection to the air duct distribution system. The heat of the motor is added to the heat delivered to the system. The solar system also includes four motorized special low leakage dampers and two gravity fabric dampers. The system is automatically controlled by a solid state controller with three thermistors: one located in the collectors, one in the rock box to plenum, one in the return air duct from the heated space. A three stage heating thermostat, located in the conditioned space, controls the operation.

Source record↗

An area model for on-chip memories and its application

An area model suitable for comparing data buffers of different organizations and arbitrary sizes is described. The area model considers the supplied bandwidth of a memory cell and includes such buffer overhead as control logic, driver logic, and tag storage. The model gave less than 10 percent error when verified against real caches and register files. It is shown that, comparing caches and register files in terms of area for the same storage capacity, caches generally occupy more area per bit than register files for small caches because the overhead dominates the cache area at these sizes. For larger caches, the smaller storage cells in the cache provide a smaller total cache area per bit than the register set. Studying cache performance (traffic ratio) as a function of area, it is shown that, for small caches, direct-mapped caches perform significantly better than four-way set-associative caches and, for caches of medium areas, both direct-mapped and set-associative caches perform better than fully associative caches.

Mulder, Johannes M.↗

Digital optical tape: Technology and standardization issues

During the coming years, digital data storage technologies will continue an aggressive growth to satisfy the user's need for higher storage capacities, higher data transfer rates and long-term archival media properties. Digital optical tape is a promising technology to satisfy these user's needs. As any emerging data storage technology, the industry faces many technological and standardization challenges. The technological challenges are great, but feasible to overcome. Although it is too early to consider formal industry standards, the optical tape industry has decided to work together by initiating prestandardization efforts that may lead in the future to formal voluntary industry standards. This paper will discuss current industry optical tape drive developments and the types of standards that will be required for the technology. The status of current industry prestandardization efforts will also be discussed.

Podio, Fernando L.↗

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗

A class Hierarchical, object-oriented approach to virtual memory management

The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.

Russo, Vincent F.↗

Effects of Carbonic Acid-Rock Interactions on CO2/Brine Multiphase Flow Properties in the Upper Minnelusa Sandstones

Summary Carbon dioxide (CO2) injection into a deep saline aquifer can dissolve into formation brine and generate carbonic acid. The resulting acid can drive fluid-rock geochemical reactions. The impact of these fluid-rock geochemical reactions on porosity, permeability, and multiphase flow responses is relevant to the determination of CO2 storage capacity of deep saline aquifers. In this research, carbonic acid flooding experiments were performed on core samples consisting of poorly sorted, quartz-rich sand with laminated bedding from a possible CO2 storage target in northwest Wyoming. Complementary pre- and post-injection porosity and permeability, thin-section, Brunauer-Emmett-Teller (BET) surface area, mercury intrusion capillary pressure (MICP), and time-domain nuclear magnetic resonance (TD-NMR) measurements were conducted. Overall, both core porosity and permeability increased after a 7-day carbonic acid injection, from 6.2 to 8.4% and 1.6 to 3.7 md, respectively. We attributed these changes to carbonate mineral dissolution, which was evidenced by the effluent brine geochemistry, pore-throat size distribution (PTSD), and BET surface area. To be more specific, within the more-permeable section of core samples containing larger pore size, the permeability increment is apparent due to dolomite mineral grains and cements dissolution. However, for the lower-permeability section corresponding to the smaller pore size, mineral precipitation possibly lessened dissolution effects, leading to insignificant petrophysical properties changes. Consequently, the observed heterogeneous carbonic acid-rock interactions resulted in alterations of CO2/brine relative permeability (i.e., the initial CO2 saturation decreased and the CO2 flow capacity was enhanced). This research provides a fundamental understanding regarding effects of fluid-rock reactions on changes in static and multiphase flow properties of eolian sandstones, which lays the foundation for more accurate prediction/simulation of CO2 injection into deep saline aquifers.

Engineering↗

Pricing and Energy Trading in Peer-to-Peer Zero Marginal-Cost Microgrids

Efforts to utilize 100% renewable energy in community microgrids require new approaches to energy markets and transactions to efficiently address periods of scarce energy supply. In this paper we contribute to the promising approach of peer-to-peer (P2P) energy trading in two main ways: analysis of a centralized, welfare-maximizing economic dispatch that characterizes optimal price and allocations, and a novel P2P system for negotiating energy trades that yields physically feasible and at least weakly Pareto-optimal outcomes. Our main results are 1) that optimal pricing is insufficient to induce agents with batteries to take optimal actions, 2) a novel P2P algorithm to addresses this while keeping private information, 3) a formal proof that this algorithm converges to the centralized solution in the case of two agents negotiating for a single period, and 4) numerical simulations of the P2P algorithm performance with up to 10 agents and 24 periods that show it converges on average to total welfare within 0.1% of the social optimum in on the order of 10s to 100s of iterations, increasing with the number of agents, time periods, and total storage capacity.

batteries↗

Reservoir Drought Resilience Under Future Warming Scenarios: Regional Disparities Across Heavily Regulated US Basins

Droughts across the U.S. have imposed substantial challenges to the management of water resources. Reservoir drought, one type of hydrological drought, is characterized by abnormally low reservoir storage levels, reflecting combined impacts of natural water shortages and water management practices. We investigate how reservoir drought signatures, particularly onset, severity, duration, recovery and frequency, may shift under rising temperatures, and how these shifts vary by reservoir typology and degree of regulation. By coupling atmosphere-land-river models with reservoir operations at ~12-km resolution, we simulated reservoir storage and characterized reservoir droughts across five heavily regulated U.S. basins. Our findings reveal significant regional and functional disparities in reservoir drought resilience under the scenario of rising temperatures. Reservoirs in the Texas-Gulf region are projected to become more resilient, while systems in the Upper Colorado and South Atlantic-Gulf regions face increased risk due to prolonged drought durations and slower recovery. With respect to primary function, reservoirs used for irrigation and hydropower, particularly those with smaller storage capacity and lower degrees of regulation, are most susceptible to future drought stress. These results are valuable in understanding water availability in highly regulated environments, and the influence of hydrometeorological conditions on storage dynamics. Overall, this study provides the first of its kind benchmark for reservoir droughts at a continental scale to support evolving multi-sectoral drought mitigation efforts. Future research is needed to link reservoir drought conditions to actual supply shortages across competing water uses, while leveraging existing adaptive management strategies and coordinated reservoir operations.

reservoir↗

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗

Exploring Future Storage Options for ATLAS at the BNL/SDCC facility

The ATLAS experiment is expected to deliver an unprecedented amount of scientific data in the High Luminosity(HL-LHC) era. As the demand for disk storage capacity in ATLAS continues to rise steadily, the BNL Scientific Data and Computing Center (SDCC) faces challenges in terms of cost implications for maintaining multiple disk copies and adapting to the coming ATLAS storage requirements. To address these challenges, the SDCC Storage team has undertaken a thorough analysis of the ATLAS experiment's requirements, matching them to suitable storage options and strategies, and has explored alternatives to enhance or replace the current storage solution. This paper aims to present the main challenges encountered while supporting big data experiments such as ATLAS. We describe the experiment's specific requirements and priorities, particularly focusing on the critical storage system characteristics of the high-luminosity run and how the key storage components provided by the Storage team work together: the dCache disk storage system; its archival back-end, HPSS; and its OS-level backend Storage. Specifically, we investigate a novel approach to integrate Lustre and XRootD. In this setup, Lustre serves as backend storage and XRootD acts as an access layer frontend, supporting various grid access protocols. Additionally, we also describe the validation and commissioning tests, including the performance comparison between dCache and XRootd. Furthermore, we provide a performance and cost analysis comparing OpenZFS and LINUX MD RAID, evaluate different storage software stacks, and showcase stress tests conducted to validate Third Party Copy (TPC) functionality.

99 GENERAL AND MISCELLANEOUS↗

Enhanced Long-Duration Energy Storage Modeling [Slides]

As our power grid evolves toward a more renewable future, energy storage is poised to take a larger role in meeting growing energy needs. Energy storage could help keep the power system reliable even through potential outages, periods of extreme weather, and when generation from variable renewable technologies like wind and solar is low. Given the different durations of these stressors, grid analysts at the National Renewable Energy Laboratory (NREL) are working to better understand the role and benefits of long-duration energy storage - or storage technologies with 8-24 hours of storage capacity - in high variable renewable energy systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗