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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗
DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

dCache: from Resilience to Quality of Service

A major goal of future dCache development will be to allow users to define file Quality of Service (QoS) in a more flexible way than currently available. This will mean implementing what might be called a QoS rule engine responsible for registering and managing time-bound QoS transitions for files or storage units. In anticipation of this extension to existing dCache capabilities, the Resilience service, which maintains on-disk replica state, needs to undergo both structural modification and generalization. This paper describes ongoing work to transform Resilience into the new architecture which will eventually support a more broadly defined file QoS.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Generator Interconnection Costs to the Transmission System in non-ISO Balancing Authorities [Slides]

Electric transmission system operators—including Independent System Operators (ISOs), Regional Transmission Organizations (RTOs), and utilities—require proposed power plants to undergo a series of interconnection studies before connecting to the grid. These studies assess what transmission upgrades or new infrastructure may be necessary and assign the associated costs to the project. Lawrence Berkeley National Laboratory has compiled, aggregated, and cleaned interconnection cost data, originally for ISOs/RTOs, and now for five non-ISO Balancing Authorities: PacifiCorp, Bonneville Power Authority, Duke Energy Progress, Duke Energy Carolinas and Duke Energy Florida. Insufficient transparency in interconnection cost data may contribute to rapidly expanding interconnection queues, with active queue capacities tripling between 2020 and 2024 in the studied BAs. Most projects withdraw after receiving high interconnection cost estimates. Interconnection costs have increased since the early 2000s, with average costs for "complete" projects reaching $194/kW between 2018 and 2024. Active queue projects and withdrawn projects incur substantially higher costs, primarily due to rising network upgrade costs. Recent interconnection costs in non-ISO balancing authorities are higher than in ISO regions, potentially due to a greater willingness to pay among developers. Utility-scale solar, wind, and storage projects have interconnection costs that exceed those for natural gas. However, when focusing on projects that do not withdraw from the queue, the interconnection costs for these technologies are more similar to natural gas projects. Other key findings include: (1) Larger generation projects benefit from lower proportional interconnection costs, (2) capacity transmission service (NRIS) often requires additional network investments, and (3) projects with high network upgrade costs are often clustered geographically. The dataset includes results from 2,104 interconnection studies conducted between 2000 and 2024, covering projects that are operational, withdrawn, or still progressing through the study process. The Excel file contains (a) the complete project-level interconnection cost dataset, and (b) seven additional tabs summarizing cost metrics across dimensions such as time, market structure, cost category (point of interconnection vs. broader network upgrades), fuel type, service type (ERIS vs. NRIS), generator size, and geography.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

PDPTW-DB: MILP-Based Offline Route Planning for PDPTW with Driver Breaks

The Pickup and Delivery Problem with Time Windows (PDPTW) involves optimizing routes for vehicles to meet pickup and delivery requests within specific time constraints, a challenge commonly faced in logistics and transportation. Microtransit, a flexible and demand-responsive service using smaller vehicles within defined zones, can be effectively modeled as a PDPTW. Yet, the need for driver breaks—a key human constraint—is frequently overlooked in PDPTW solutions, despite being necessary for regulatory compliance. This study presents a novel mixed-integer linear programming formulation for the Pickup and Delivery Problem with Time Windows and Driver Breaks (PDPTW-DB). To the best of our knowledge this formulation is the first to consider mandatory periodic driver breaks within optimized Microtransit routes. The proposed model incorporates regulatory compliant break scheduling directly within the vehicle routing optimization framework. By considering driver break requirements as an integral component of the optimization process, rather than as a post-processing step, the model enables the generation of routes that respect hours of service regulations while minimizing operational costs. This integrated approach facilitates the generation of schedules that are operationally efficient and prioritize driver welfare through driver breaks. We work with a public transit agency from the southern USA, and highlight the specific nuances of driver break optimization, and present a Pickup and Delivery Problem with Time Windows formulation for optimizing Microtransit operations and scheduling driver breaks. We validate our approach using real-world data from the transit agency. Our results validate our formulation in producing cost-effective, and regulation-compliant solutions.

Applied Computing, Transportation↗
DOE OSTI2023

Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medi-um-voltage sensor is compared with a reference PT and CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the US De-partment of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that was used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, service restoration), while the analog signals were recorded by the same high resolution power meter. The behavior of analog signals, harmonic components, total harmonic distortion, and crest factors were assessed for this power line sensor compared with the reference PT/CT, because of the absence for testing standards for advanced outdoor power line sensors.

Piesciorovsky, Emilio↗
DOE OSTI2020

Real-time Simulation of Coordinated Sub-Transmission Volt-Var Control Tool under High Distributed PV Penetration

With the rapid penetration of intermittent solar photovoltaic (PV) and other distributed energy resources (DER) into the grid, and subsequent changes in power flow patterns in both distribution and sub-transmission, voltage regulation is becoming a major challenge. It is prudent to leverage PV and DER to provide ancillary services to the grid, such as voltage regulation. Recently, a quasi-static, coordinated real-time sub transmission volt-var control algorithm (CReST-VCT) was developed for voltage regulation under high PV penetration by dispatching the reactive power settings of the shunt devices and PV inverters. The algorithm was validated offline, on a quasistatic study. Such quasi-static dispatching algorithms cannot guarantee its performance for highly nonlinear dynamical power systems. In this paper the performance of the algorithm is validated with a real time nonlinear dynamic simulation of a modified IEEE 118 bus system in Opal-RT. The real time simulation is used to emulate the actual system operation, providing a more realistic testing environment for CReST-VCT. The dispatch and control signals are communicated between the power system (Opal solver) and the control center (GAMS solver) in real-time with a MODBUS bridge. The results demonstrate i) system is stable with the new dispatch points ii) significant improvement in system-wide voltage profiles compared to an uncontrolled scenario. Another significant contribution of the work is developing a framework for dispatchable, long duration dynamic simulations that can be leveraged for market/dispatch studies.

CReST-VCT, Opal-RT, Volt/Var Control, renewable in↗
DOE OSTI2024

DuraMAT: Building a Consortium to Accelerate the Photovoltaic Module Reliability Learning Cycle

Durable and reliable photovoltaic (PV) modules are critical to enabling an efficient transition to sustainable energy generation. The rate at which new module designs and materials are developed and deployed currently outpaces the rate at which we can identify failure mechanisms and understand degradation rates. Increasing the service life of PV modules, and our ability to predict performance over time, requires more durable materials and designs, better durability testing, more extensive material characterization, robust modeling, and methods to cross-examine historical performance data to extract meaningful results. This is a multidisciplinary challenge that requires expertise from a broad range of fields and, therefore, benefits significantly from a collaborative approach. In this Perspective, we outline the approach taken by the Durable Module Materials Consortium (DuraMAT), present a few case studies where our approach was successful, and provide an outlook on where this approach might be applied as the PV technology landscape continues to rapidly evolve. Published by the American Physical Society 2024

14 SOLAR ENERGY↗
DOE OSTI2026

West Africa Battery Energy Storage Systems (BESS) Capacity Building - Discussion of BESS Tariffs: Payment Structures and Case Studies [Slides]

Battery Energy Storage Systems (BESS) are emerging as critical assets for enhancing grid reliability, integrating renewable energy, and enabling system flexibility. Yet, the regulatory and financial frameworks that determine how BESS projects are compensated vary widely across jurisdictions. This presentation explores international case studies - from Honduras, Costa Rica, Chile, South Africa, Mexico, and Brazil - to illustrate how tariff design and payment structures are evolving to support large-scale BESS deployment. The cases highlight a range of ownership and revenue models, including cost-of-service mechanisms, energy and capacity payments, and market-based arbitrage, as well as hybrid approaches under development. The discussion will examine key challenges such as defining remuneration for ancillary services, addressing double charging, and accounting for efficiency losses and degradation over time. By comparing experiences across markets, the presentation identifies emerging best practices for valuing BESS and designing tariffs that align technical performance with economic incentives, providing insights for regulators, utilities, and policymakers pursuing storage integration.

25 ENERGY STORAGE↗
DOE OSTI2020

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗
DOE OSTI2021

Orange County Transportation Authority Fuel Cell Electric Bus Progress Report (Feb-Jul 2020) [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by Orange County Transportation Authority (OCTA) in Southern California. The ten FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in late-2019, and were placed in service on February 9, 2020. The data period covers February 2020 through July 2020. NREL collects data on ten 2016 model year compressed natural gas (CNG) buses as a baseline comparison at OCTA.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Orange County Transportation Authority Fuel Cell Electric Bus Progress Report - Data Period Focus: Feb. 2020 through Jul. 2021 [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by Orange County Transportation Authority (OCTA) in Southern California. The ten FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in late-2019, and were placed in service on February 9, 2020. The data period covers February 2020 through July 2021. NREL collects data on ten 2016 model year compressed natural gas (CNG) buses as a baseline comparison at OCTA.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Insights Into On-Demand Transit: A Case Study of Houston METRO's curb2curb Service

As modern on-demand transit (ODT) deployments increase, the insights gained from studying real-world systems prove more useful. In this study, a shared ODT system called "METRO curb2curb" in the suburbs of Houston, Texas was studied, with a particular focus on the Missouri City zone, which has the highest ridership out of the four total zones. The Missouri City zone is 18 square miles with an average daily ridership of nearly 400 as of November 2024. In order to gain a passenger perspective, data collection was performed through using the ODT system first-hand, completing 50 rides in March and April of 2023. These rides included a mix of three different types of on-demand travel accommodations - 1.) advance bookings (30 min - 2 hours ahead), 2.) as-soon-as-possible / real-time dispatch bookings, and 3.) no-reservation trips at two designated "anchor points." Wait and travel time were collected for each ride. Anecdotal findings related to ease of locating the driver/vehicle, the process of booking a ride, and popular trip purposes were also documented. This study provides an overview of the METRO curb2curb system, including its history, service provider, service area, ridership, booking options, wait time, and travel time. Intricacies related to different definitions of wait time are included. Finally, relevant considerations for automating the on-demand transit system and discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Reduced Contracting Time To Accelerate Construction: A Streamlined Approach for Speed and Scale

In the fast-paced construction world, efficiency isn't just an advantage - it's a necessity. By implementing the Cooperative Construction Contracting Agreement (CCCA), we are transforming how we approach major projects, replacing traditional multistep contracting with a streamlined, one-step process. This innovative contracting approach saves valuable time and resources, enabling us to accelerate delivery across our portfolio of projects. Under the old model, each construction phase required separate competitive solicitations for design, build, and other services. With the CCCA, we've consolidated these steps, working with a trusted partner from start to finish. This results in significant time savings that translate into faster project execution without compromising quality or safety.

collaborative partnerships↗
DOE OSTI2025

Insights Into On-Demand Transit: A Case Study of Houston METRO's curb2curb Transit Services: Preprint

As modern on-demand transit (ODT) deployments increase, the insights gained from studying real-world systems prove more useful. In this study, a shared ODT system called "METRO curb2curb" in the suburbs of Houston, Texas was studied, with a particular focus on the Missouri City zone, which has the highest ridership out of the four total zones in which the system operates. The Missouri City zone spans 18 square miles with an average daily ridership of nearly 400 as of November 2024. In order to gain a passenger perspective, data collection was performed through using the ODT system first-hand, completing 50 rides in March and April of 2023. These rides included a mix of three different types of on-demand travel accommodations - 1.) advance bookings (30 min - 2 hours ahead), 2.) as-soon-as-possible / real-time dispatch bookings, and 3.) no-reservation trips at two designated "anchor points." Wait and travel time were collected for each ride. Anecdotal findings related to ease of locating the driver/vehicle, the process of booking a ride, and popular trip purposes were also documented. This study provides an overview of the METRO curb2curb system, including its history, service provider, service area, ridership, booking options, wait time, and travel time. Intricacies related to different definitions of wait time are included. Finally, relevant considerations for automating the on-demand transit system and discussed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Dynamic Line Rating Forecast Time Frames

As dynamic line ratings (DLR) are used to support different use cases, the preferred data source varies according to the forecast horizon. The below guidance is one possibility to utilize weather forecasting. Note that the time-periods of forecasts and spatial resolution may be subject to change as National Oceanic and Atmospheric Administration (NOAA)/National Weather Service (NWS) periodically upgrades its forecast models and data servers. Moreover, Persistence/ML Observations advances in analytics may justify combining data sources for more reliable DLR forecasts. The list below gives a time period (t) followed by possible guidance for data in that interval.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Adaptive Protection of Scientific Backbone Networks Using Machine Learning

In this article, we propose a new protection scheme for backbone networks to guarantee high service availability. The presented scheme does not require any reconfiguration immediately after the failure (i.e., it is proactive). At the same time, it does not require any reserved backup network resources either. To achieve these seemingly contradictory goals, we utilize the recent advancements in Machine Learning (ML) to implement a network intelligence that periodically re-allocates the unused capacity as protection bandwidth to meet the service availability requirements of each connection. Our goal is achieved by two components (1) predicting the traffic for the next period on each link, and (2) intelligently selecting the best fit dedicated protection scheme for the next period depending on the estimated unused (spare) bandwidth and the previous service availability violations. Note that re-allocating protection bandwidth affects neither the operational connections nor the current best practice of operators to over-provision network bandwidth to support elephant flows. Finally, we provide a case study on the real traffic from Energy Sciences Network (ESnet), a high-speed, international scientific backbone network. The key benefit of our framework is that adaptively utilizing the over-provisioned bandwidth for spare capacity is sufficient to improve the availability from three-nines to five-nines (in ESnet for the 30 examined connections). The drawback is negligible bandwidth limitations; the user perceives a minor and very temporal bandwidth limitation in less than 0.1% of the time.

42 ENGINEERING↗
DOE OSTI2024

Community Public Mobility Using On-Demand, Low-Speed Electric Vehicles: A Case Study in Downtown St. Louis, Missouri

Legacy fixed route transit systems designed to serve commuters struggle to provide efficient and effective service for short neighborhood trips and for population groups unable to access and egress transit stops using active modes (e.g., elderly, disabled). Neighborhood on-demand transit (ODT) services using low-speed electric vehicles (LSEV) are an innovative technological solution that can help fill this gap in service (e.g., short, high-frequency trips) for diverse populations and trip types. This study evaluated user characteristics and travel behavior for a neighborhood ODT service (using LSEVs) in downtown St. Louis, Missouri using responses from a community survey (n=244), ridership data, and vehicle trajectory information. A comparative analysis between neighborhood ODT, fixed route transit, and transportation network companies (TNC) was also conducted from the perspectives of total travel time, cost, and greenhouse gas emissions. Ultimately, the goal of the analysis was to motivate and inform holistic public mobility systems where different services are optimized to meet specific community needs. Findings indicate that the neighborhood ODT was effective at reaching diverse populations (elderly (20%), lower income (27%), and households with limited access to private vehicles (34%)). ODT reduced total travel time by 32% compared to fixed route transit, produced 2.4 - 4.3 times less greenhouse gas emissions per passenger mile (compared to transit and TNCs), and was more affordable (free to users) than alternative options ($1 for transit, $10-12 for TNCs). Overall satisfaction rates were high, with 80% of respondents rating the service a 4 or 5 out of 5.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗