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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Change in Brooklyn and Queens: How New York?s Reforming the Energy Vision Program and Con Edison Are Reshaping Electric Distribution Planning

The New York City boroughs of Brooklyn and Queens are undergoing a period of gentrification, infrastructure rebuilding, new construction, and load growth not experienced in decades. Significant numbers of residents are moving in, and structures that had been abandoned or were in disrepair are being refurbished and modernized to accommodate the burgeoning population. Homes, businesses, and industries are reviving areas long in decline, and Brooklyn's growth has made it the nation's fourth most populous city, according to the U.S. Census Bureau.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Funding Proposal for EDISON’20 Conference Buffalo, New York, 07/17 - 07/21, 2017

EDISON’20 – The 20th International Conference on Electron Dynamics in Semiconductors, Optoe- lectronics and Nanostructures – was held at the Hyatt Regency Hotel, Buffalo, NY from July 17 – 21, 2017. The technical focus of this conference was on the fundamental physics and applications of nonequilibrium classical and quantum carrier dynamics in semiconductors, optoelectronic de- vices, and nanostructures. This five-day, single-session conference featured a program consisting of some 15 invited talks, given by internationally-renowned academics from the U.S., Europe, and Japan. Their keynote presentations covered topics including: terahertz phenomena in semiconductors; quantum transport in novel two-dimensional semiconductors; topological insulators; mesoscopic phenomena in semiconductors, and; semiconductor spintronics. The invited papers were supplemented by some 30 contributed talks, selected from almost 120 abstracts submitted in response to the conference’s call for papers, and by two poster sessions that each consisted of close to 40 different reports. This critical mass in terms of scientific content ensured a highly vibrant conference, in which leaders in the field had the opportunity to interact closely with early-career scientists.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Transactive Approach for Engaging Distribution Network Assets for Voltage Management in Southern California Edison Distribution Feeders

This report documents an effort by Pacific Northwest National Laboratory (PNNL) investigating the utility of using incentive signals to elicit useful responses from smart inverters associated with customer-owned distributed energy resources (DERs). This project was an element of the Southern California Edison (SCE) Integrated Grid Project (IGP) funded by the California Public Utilities Commission’s (CPUC’s) Electric Program Investment Charge (EPIC) program (CPUC 2018) to support applied research and development, technology demonstration and deployment, and the market facilitation of clean energy technologies and approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Commonwealth Edison (ComEd) Chicago Best Practices: Energy Data Accelerator

This case study describes how Commonwealth Edison (ComEd) and the city of Chicago worked together to develop a way for commercial building owners to get access to whole-building energy data more efficiently. This would enable building owners to comply with local energy benchmarking ordinances.

local government, utility, energy data, data acces↗
DOE OSTI2018

Exploring New Models for Utility Distributed Energy Resource Planning and Integration: SMUD and Con Edison

As a result of the rapid growth of renewable energy in the United States, the U.S. electric grid is undergoing a monumental shift away from its historical status quo. These changes are occurring at both the centralized and local levels and have been driven by a number of different factors, including large declines in renewable energy costs, federal and state incentives and mandates, and advances in the underlying technology. Higher levels of variable-generation renewable energy, however, may require new and increasingly complex methods for utilities to operate and maintain the grid while also attempting to limit the costly build-out of supporting grid infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Battery Performance, Thermal, and Life Modeling for Southern California Edison (Cooperative Research and Development Final Report)

The objective of this project is to develop battery performance models, thermal models and life models for SCE to use in simulation and analysis of grid services involving energy storage. NREL will fit the models to three separate chemistries using test data provided by SCE. The dataset for each chemistry will include electrical, thermal and aging response to different temperatures and cycling conditions, measured under a variety of cell-level and module-level experiments described in SCE test protocol documents. Once tuned to a test dataset, the battery system model software will provide predictions of battery energy and power loss, and thus cycle and calendar life, for any energy storage grid service power profile of interest to SCE. The automated battery life modeling and simulation tool can also be applied to any other grid battery systems as long as necessary input data is available to accelerate battery model development and battery lifetime analysis.

25 ENERGY STORAGE↗
DOE OSTI2018

Towards understanding HPC users and systems: A NERSC case study

High performance computing (HPC) scheduling landscape currently faces new challenges due to thechanges in the workload. Previously, HPC centers were dominated by tightly coupled MPI jobs. HPCworkloads increasingly include high-throughput, data-intensive, and stream-processing applications. Asa consequence, workloads are becoming more diverse at both application and job levels, posing newchallenges to classical HPC schedulers. There is a need to understand the current HPC workloads andtheir evolution to facilitate informed future scheduling research and enable efficient scheduling in futureHPC systems.In this paper, we present a methodology to characterize workloads and assess their heterogeneity,at a particular time period and its evolution over time. We apply this methodology to the workloads ofthree systems (Hopper, Edison, and Carver) at the National Energy Research Scientific Computing Center(NERSC). We present the resulting characterization of jobs, queues, heterogeneity, and performance thatincludes detailed information of a year of workload (2014) and evolution through the systems’ lifetime(2010–2014).

Rodrigo, Gonzalo P.↗
DOE OSTI2016

Adaptive Transmission Planning: Implementing a New Paradigm for Managing Economic Risks in Grid Expansion

The problem of whether, where, when, and what type of transmission facilities to build in terms of minimizing costs and maximizing net economic benefits has been a challenge for the power industry from the beginning-ever since Thomas Edison debated whether to create longer dc distribution lines (with their high losses) or build new power stations in expanding his urban markets. Today's planning decisions are far more complex, as grids cover the continent and new transmission, generation, and demand-side technologies are emerging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Towards Real-Time Detection and Tracking of Spatio-Temporal Features: Blob-Filaments in Fusion Plasma [Spatio-Temporal Features in Large Irregular Data: Blob-Filaments in Fusion Plasma]

This work was originally motivated the need to identify and track blob filaments, a feature often associated with instability in magnetically confined fusion plasma. Understanding and mitigating such instability would improve fusion reactors and make fusion a truly inexhaustible source of clean energy. Similar spatio-temporal features are important in many other applications, for example, ignition kernels in combustion and tumor cells in a medical image. This work presents an approach for extracting these features by dividing the overall task into three steps: local identification of feature cells, grouping feature cells into extended feature, and tracking movement of feature through overlapping in space. Through our extensive work in parallelization, we demonstrate that this approach can effectively make use of a large number of compute nodes to detect and track blobs in fusion plasma. On a set of 4.3TB data, we observed linear speedup on 1024 processes and completed blob detection in less than three milliseconds using Edison, a Cray XC30 system at NERSC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Low-cost embedded optical sensing systems for distribution transformer monitoring

There is a mounting need for low-cost monitoring with online sensing technologies to maintain grid reliability and uptime. Here we introduce an innovative low-cost, embedded optical sensing technology initially focused on transformers that was developed and demonstrated at a major electric utility, Con Edison. A version of it that can be retrofitted onto existing transformers in the field was also developed. Two new 500 kVA distribution network transformers were built with embedded fiber-optic (FO) sensors and qualified per industry standards. Vibration, temperature, and corrosion were key parameters monitored. The first transformer with embedded FO sensors was installed at a Con Edison facility and monitored at our team’s office. The second one was installed in an urban street-side underground location with online data processing/feature extraction algorithms and monitored through a wireless router. Additionally, an older transformer was also retrofitted. Data analysis was done on these transformers showing promising correlations with their corresponding loading cycles. Furthermore, key events such as the transformer primary-side energizing, and other events were detected. In general, the technology was demonstrated over 6 months across the 3 transformers instrumented with promising results. Thus, it has the potential to enable predictive maintenance for transformers and other grid assets.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

High-performance epistasis detection in quantitative trait GWAS

epiSNP is a program for identifying pairwise single nucleotide polymorphism (SNP) interactions (epistasis) in quantitative-trait genome-wide association studies (GWAS). A parallel MPI version (EPISNPmpi) was created in 2008 to address this computationally expensive analysis on large data sets with many quantitative traits and SNP markers. However, the falling cost of genotyping has led to an explosion of large-scale GWAS data sets that challenge EPISNPmpi’s ability to compute results in a reasonable amount of time. Therefore, we optimized epiSNP for modern multi-core and highly parallel many-core processors to efficiently handle these large data sets. This paper describes the serial optimizations, dynamic load balancing using MPI-3 RMA operations, and shared-memory parallelization with OpenMP to further enhance load balancing and allow execution on the Intel Xeon Phi coprocessor (MIC). For a large GWAS data set, our optimizations provided a 38.43× speedup over EPISNPmpi on 126 nodes using 2 MICs on TACC’s Stampede Supercomputer. We also describe a Coarray Fortran (CAF) version that demonstrates the suitability of PGAS languages for problems with this computational pattern. We show that the Coarray version performs competitively with the MPI version on the NERSC Edison Cray XC30 supercomputer. Finally, the performance benefits of hyper-threading for this application on Edison (average 1.35× speedup) are demonstrated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

MPAS-Ocean NESAP Status Report

NESAP performance improvements on MPAS-Ocean have resulted in a 5% to 7% speed-up on each of the examined systems including Cori-KNL, Cori-Haswell, and Edison. These tests were configured to emulate a production workload by using 128 nodes and a high-resolution ocean domain. Overall, the gap between standard and many-core architecture performance has been narrowed, but Cori-KNL remains considerably under-performing relative to Edison. NESAP code alterations affected 600 lines of code, and most of these improvements will benefit other MPAS codes (sea ice, land ice) that are also components within ACME. Modifications are fully tested within MPAS. Testing in ACME across many platforms is underway, and must be completed before the code is merged. In addition, a ten-year production ACME global simulation was conducted on Cori-KNL in late 2016 with the pre-NESAP code in order to test readiness and configurations for scientific studies. Next steps include assessing performance across a range of nodes, threads per node, and ocean resolutions on Cori-KNL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Grid Ready: Strategies for Interconnecting Large-Scale PV in New York City

This Grid Ready Solar project is intended to help create transparency for building owners and developers, so they can better understand and more quickly navigate the interconnection process for large-scale photovoltaic (PV) projects on Con Edison's electrical grid in New York City. Phase 1 of the project provided high-level technical screens of grid interconnection requirements in an attempt to streamline the interconnection of large-scale solar PV systems to the New York City grid. In Phase 2 of the Grid Ready project, the focus of this report, Sustainable CUNY worked with NREL to evaluate a range of solutions for improving the economics of large-scale (over 200 kW) PV within the five boroughs of New York City that are in Con Edison's service territory, as identified on the NY Solar Map.

14 SOLAR ENERGY↗
DOE OSTI2026

ICE Calculator 2: Final Report for Phase 1 and 2 of the National Initiative to Update the Interruption Cost Estimate (ICE) Calculator

ICE 2.0 Phase 2 Final Report In 2021, Berkeley Lab and Resource Innovations, Inc. launched the “ICE Calculator 2 Initiative” – a national study to refresh the underlying data and enhance the functionality of the ICE Calculator. The Initiative involves Berkeley Lab contracting with sponsoring utilities to administer identical, updated and comprehensive interruption cost surveys to statistically representative samples of each utility’s customers. Berkeley Lab and Resource Innovations then pool the survey results across the utilities and use them to update the analytical engines that drive the ICE Calculator. The ICE Calculator 2 Initiative is being conducted in phases. Each phase involves the administration of interruption cost surveys to the customers of sponsoring utilities, followed by an update to the ICE Calculator based on analysis of the pooled survey results. This report describes the activities and findings from Phase 1 and 2 of the ICE Calculator 2 Initiative. Phase 1 was sponsored by eight utilities: American Electric Power, Commonwealth Edison, Dominion Energy, Duke Energy, DTE Electric, Exelon, National Grid, and Puget Sound Energy. Phase 2 was sponsored by six utilities: Empire District Electric Company, Evergy Missouri, Pacific Gas & Electric, San Diego Gas & Electric, Southern California Edison, and Union Electric. Phase 1 and 2 involved 15 customer interruption cost survey activities representing a total of 30 electricity distribution service territories. ICE Calculator Version 2.0 and 2.2 Comparison This memorandum describes–at a high-level–the improvements in interruption cost estimates for the version 2.2 of the ICE Calculator (released February 2026) compared to version 2.0 (released in April 2025). Version 2.2 of the ICE Calculator corresponds to Phase 2 of the initiative, while version 2.0 corresponds to Phase 1. The improvements in version 2.2 result from both a significant increase in the number of customer responses that have been collected and the identification of seven additional factors that help estimate customer interruption costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems

Parallel I/O hardware and software infrastructure is a key contributor to performance variability for applications running on large-scale HPC systems. This variability confounds efforts to predict application performance for characterization, modeling, optimization, and job scheduling. We propose a modeling approach that improves predictive ability by explicitly treating the variability and by leveraging the sensitivity of application parameters on performance to group applications with similar characteristics. We develop a Gaussian process-based machine learning algorithm to model I/O performance and its variability as a function of application and file system characteristics. We demonstrate the effectiveness of the proposed approach using data collected from the Edison system at the National Energy Research Scientific Computing Center. The results show that the proposed sensitivity-based models are better at prediction when compared with application-partitioned or unpartitioned models. We highlight modeling techniques that are robust to the outliers that can occur in production parallel file systems. Using the developed metrics and modeling approach, we provide insights into the file system metrics that have a significant impact on I/O performance.

I/O performance variability↗