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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 289 records · Page 16
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DOE OSTI2017

An Overview of the Automated Dispatch Controller Algorithms in the System Advisor Model (SAM)

Three automatic dispatch modes have been added to the battery model within the System Adviser Model. These controllers have been developed to perform peak shaving in an automated fashion, providing users with a way to see the benefit of reduced demand charges without manually programming a complicated dispatch control. A flexible input option allows more advanced interaction with the automated controller. This document will describe the algorithms in detail and present brief results on its use and limitations.

25 ENERGY STORAGE↗
DOE OSTI2025

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗
DOE OSTI2016

Predictive Battery Management System for Commercial Hybrid Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-13-520

NREL and Eaton Corporation will perform work together on DOE Advanced Research Projects Agency-Energy (ARPA-E) 'Advanced Management and Protection of Energy Storage Devices' program (DE-FOA0000675). NREL will experimentally characterize aging behavior of Eaton cells and packs. Eaton and NREL will implement NREL's prognostic life model in Eaton HEV supervisory controllers and demonstrate the algorithms in accelerated life hardware-in-the loop testing conducted at NREL.

25 ENERGY STORAGE↗
DOE OSTI2022

Revenue prediction for integrated renewable energy and energy storage system using machine learning techniques

Revenue estimation for integrated renewable energy and energy storage systems is important to support plant owners or operators’ decisions in battery sizing selection that leads to maximized financial performances. A common approach to optimizing revenues of a hybrid hydro and energy storage system is using mixed-integer linear programming (MILP). Although MILP models can provide accurate production cost estimations, they are typically very computationally expensive. To provide a fast yet accurate first-step information to hydropower plant owners or operators who consider integrating energy storage systems, we propose an innovative approach to predicting optimal revenues of an integrated energy generation and storage system. In this study, we examined the performance of two prediction techniques: Generalized Additive Models (GAMs) and machine learning (ML) models developed based on artificial neural networks (ANN). Predictive equations and models are generated based on optimized solutions from a market participation optimization model, the Conventional Hydropower Energy and Environmental Resource System (CHEERS) model. The two predicting techniques reduce the computational time to evaluate annual revenue for one set of battery configurations from 3 h to 1 to 4 min per run while also being implementable with significantly less data. The model validation prediction errors of developed GAMs and ML models are generally below 5%; for model testing predictions, the ML models consistently outperform the regression equations in terms of root mean square errors. This new approach allows plant owners, operators, or potential investors to quickly access multiple battery configurations under different energy generation and market scenarios. This new revenue prediction method will therefore help reduce the barriers, and thereby promoting the deployment of battery hybridization with existing renewable energy sources.

13 HYDRO ENERGY↗
DOE OSTI2016

Overview of the DOE hydrogen safety, codes and standards program, part 3: Advances in research and development to enhance the scientific basis for hydrogen regulations, codes and standards

Hydrogen fuels are being deployed around the world as an alternative to traditional petrol and battery technologies. As with all fuels, regulations, codes and standards are a necessary component of the safe deployment of hydrogen technologies. There has been a focused effort in the international hydrogen community to develop codes and standards based on strong scientific principles to accommodate the relatively rapid deployment of hydrogen-energy systems. The need for science-based codes and standards has revealed the need to advance our scientific understanding of hydrogen in engineering environments. Here, this brief review describes research and development activities with emphasis on scientific advances that have aided the advancement of hydrogen regulations, codes and standards for hydrogen technologies in four key areas: (1) the physics of high-pressure hydrogen releases (called hydrogen behavior); (2) quantitative risk assessment; (3) hydrogen compatibility of materials; and (4) hydrogen fuel quality.

08 HYDROGEN↗
DOE OSTI2023

Reinforcement learning-based design of shape-changing metamaterials

During the last decade, artificially architected materials have been designed to obtain properties unreachable by naturally occurring materials, whose properties are determined by their atomic structure and chemical composition. In this work, we implement a new reinforcement learning (RL) method able to rationally design unique metamaterial structures at the nano-, micro-, and macroscale, which change shape during operational conditions. As an example, we apply this method to design nanostructured silicon anodes for Li-ion batteries (LIBs). The RL model is designed to apply different actions and predict change during operational conditions. The multi-component reward function comprises an increase in the total storage capacity of the resulting battery electrode and structural parameters, such as the minimum distance between the individual components of the nanostructure. Upon experimental validation using a polymer-based 3D printing technique, we expect that the newly discovered structures improve the current Si-based LIB anodes state-of-the-art by almost three times and almost ten times the current commercial LIB based on a graphitic anode. Furthermore, this RL-based optimization method opens up vast design space for other responsive metamaterials with tailored properties and pre-programmed structural transformation.

25 ENERGY STORAGE↗
DOE OSTI2015

Temporal Characterization of Hydrates System Dynamics beneath Seafloor Mounds. Integrating Time-Lapse Electrical Resistivity Methods and In Situ Observations of Multiple Oceanographic Parameters

This study was designed to investigate temporal variations in hydrate system dynamics by measuring changes in volumes of hydrate beneath hydrate-bearing mounds on the continental slope of the northern Gulf of Mexico, the landward extreme of hydrate occurrence in this region. Direct Current Resistivity (DCR) measurements were made contemporaneously with measurements of oceanographic parameters at Woolsey Mound, a carbonate-hydrate complex on the mid-continental slope, where formation and dissociation of hydrates are most vulnerable to variations in oceanographic parameters affected by climate change, and where changes in hydrate stability can readily translate to loss of seafloor stability, impacts to benthic ecosystems, and venting of greenhouse gases to the water-column, and eventually, the atmosphere. We focused our study on hydrate within seafloor mounds because the structurally-focused methane flux at these sites likely causes hydrate formation and dissociation processes to occur at higher rates than at sites where the methane flux is less concentrated and we wanted to maximize our chances of witnessing association/dissociation of hydrates. We selected a particularly well-studied hydrate-bearing seafloor mound near the landward extent of the hydrate stability zone, Woolsey Mound (MC118). This mid-slope site has been studied extensively and the project was able to leverage considerable resources from the team’s research experience at MC118. The site exhibits seafloor features associated with gas expulsion, hydrates have been documented at the seafloor, and changes in the outcropping hydrates have been documented, photographically, to have occurred over a period of months. We conducted observatory-based, in situ measurements to 1) characterize, geophysically, the sub-bottom distribution of hydrate and its temporal variability, and 2) contemporaneously record relevant environmental parameters (temperature, pressure, salinity, turbidity, bottom currents) to detect short-term changes within the hydrates system, identify relationships/impacts of local oceanographic parameters on the hydrates system, and improve our understanding of how seafloor instability is affected by hydrates-driven changes. A 2009 DCR survey of MC118 demonstrated that we could image resistivity anomalies to a depth of 75m below the seafloor in water depths of 1km. We reconfigured this system to operate autonomously on the seafloor in a pre-programmed mode, for periods of months. We designed and built a novel seafloor lander and deployment capability that would allow us to investigate the seafloor at potential deployment sites and deploy instruments only when conditions met our criteria. This lander held the DCR system, controlling computers, and battery power supply, as well as instruments to record oceanographic parameters. During the first of two cruises to the study site, we conducted resistivity surveying, selected a monitoring site, and deployed the instrumented lander and DCR, centered on what appeared to be the most active locations within the site, programmed to collect a DCR profile, weekly. After a 4.5-month residence on the seafloor, the team recovered all equipment. Unfortunately, several equipment failures occurred prior to recovery of the instrument packages. Prior to the failures, however, two resistivity profiles were collected together with oceanographic data. Results show, unequivocally, that significant changes can occur in both hydrate volume and distribution during time periods as brief as one week. Occurrences appear to be controlled by both deep and near-surface structure. Results have been integrated with seismic data from the area and show correspondence in space of hydrate and structures, including faults and gas chimneys.

58 GEOSCIENCES↗
DOE OSTI2013

Michigan: Michigan's Clean Energy Resources and Economy [Brochure]

By harnessing its abundant supply of conventional hydroelectric power, biomass, and wind, Michigan is well on its way to meeting its goal, set by the 2008 Clean Renewable and Efficient Energy Act, of generating 10% of retail electricity from renewable sources by 2015. Renewable biomass accounted for 39% of renewable energy credits certified in Michigan between 2009 and 2011, thanks in part to Michigan’s 19 million acres of forest land. Small hydroelectric plants, landfill gas, and municipal solid waste are all important sources of renewable electricity in Michigan—together accounting for 34% of renewable energy credits during the same time period. Michigan also has significant undeveloped wind energy potential. Michigan also requires electric providers to develop and fund “energy optimization” programs aimed at reducing electricity consumption. Michigan is one of the few states to count efficiency as an eligible clean energy resource, awarding “energy optimization credits” for successfully reducing energy consumption. Energy optimization credits can be substituted for renewable energy credits. As of December 2009, all utility customers in Michigan are eligible to participate in at least one energy-efficiency program offered through a local utility, and aggregate statewide funding for energy optimization programs has more than tripled from $\$$67 million in 2009 to $\$$208 million in 2011. Michigan is becoming a center for the domestic advanced battery industry. Companies all along the battery supply chain cluster in the state and draw from a talented pool of scientists, engineers, and other skilled workers with decades of experience in the auto industry. Michigan’s geographic position makes the state an attractive site for wind industry manufacturing; 2010 counted 31 wind technology manufacturing facilities in the state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

New Jersey: New Jersey's Clean Energy Resources and Economy [Brochure]

New Jersey’s two currently predominant renewable energy resources are wind and solar, as evidenced by rapid market growth in both areas. As the state carries almost 100,000 megawatts of wind potential on land and offshore—enough to generate all of the current electricity needs of the state—it is no surprise that New Jersey is home to six facilities that manufacture components for wind turbines. Solar photovoltaic growth is also considerable, and at 1,000 megawatts, the state now ranks second in the nation in terms of installed capacity. In large part, this growth has been due to state policies that facilitate solar system installation (such as net metering) and state sales tax and rebate incentives for renewables. The state has committed to generating 22.5% of its electricity from renewable sources by 2021 through its Renewable Energy Portfolio Standard. In 2010, utility companies in New Jersey also invested an impressive $\$$198 million in energy efficiency and recorded savings of 497 million kilowatt hours or enough electricity to power more than 43,000 homes for one year. The utilities’ investment supports four grant programs for energy efficiency offered by New Jersey’s Public Service Electric & Gas Company, as well as a loan program and a rebate program offered by New Jersey Natural Gas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

CalTestBed - OnTo Technology - Characterization of Recycled Cathode and Anode Particles as a Function of Process Step (Final Report)

Onto Technology carries out advanced Li-ion battery recycling for industry and. has the only patented technology to produce manufacturing quality electrode materials from recycled batteries. The technology can resolve ongoing cost problems for the industry in life-cycle and conservation of critical materials. Under the Cal TestBed program, Onto Technology teamed with principal investigators at Lawrence Berkeley National Laboratory, who performed tests to evaluate the electrochemical performance of refurbished electrode materials. Other tests to determine structure and morphology of the refurbished materials carried out at LBNL included X-ray diffraction (XRD) and scanning electron microscopy (SEM).

36 MATERIALS SCIENCE↗
DOE OSTI2025

Incident Energy Systems Model: User Guide and Examples

U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day.

14 SOLAR ENERGY↗
DOE OSTI2022

Resilience with Renewables

This presentation is intended for the DOE Better Buildings Sustainable Corrections Infrastructure Partnership (SCIP) program webinar series. It will explain the INL Resilience Framework, discuss how to apply it for building managers, and give examples of the ways batteries can aid in resilience by walking through a case study conducted for Iowa Lakes Electric Cooperative.

17 WIND ENERGY↗
DOE OSTI2024

Wide Bandgap Generation (WBGen): Developing the Future Wide Bandgap Power Electronics Engineering Workforce

This Final Technical Report (FTR) summarizes the work conducted at the Center for Power Electronics Systems (CPES) under the Wide-Bandgap Generation (WBGen) fellowship and traineeship program established by the Advanced Manufacturing and Technologies Office (AMMTO) of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy (EERE) at Virginia Tech, which had as main objective to train the next generation of U.S. citizen power engineers with wide-bandgap (WBG) power semiconductor expertise, with the intent to aid in fulfilling the future workforce needs in this field. The latter was deemed of strategic importance given the fast-paced growth observed—and predicted—in the demand of this technical expertise, whose practitioners have become the enablers and executioners of the electrification transformation process that not just the U.S., but the whole world, is currently undergoing as it seeks for more effective and efficient ways to use energy. As such, the WBGen program set forth to achieve its educational goals, which in addition sought to broaden the range of WBG-based power electronics by conducting research and development on high-efficiency grid apparatus and high-efficiency electrical power systems, and to also enhance the power engineering curriculum by formalizing WBG-oriented design procedures replacing existent yet now obsolete design procedures developed for Silicon (Si) based power electronics. This effort led CPES to spearhead the development of a new major within The Bradley Electrical and Computer Engineering (ECE) Department at Virginia Tech, namely Electronic Power and Energy Systems (EPES), which coalesced power electronics and power systems courses to provide undergraduate students with a strong formation in the power engineering field, while creating a pipeline of graduate students that could pursue the WBG-based curriculum and conduct research at CPES. In all, in what is considered a true success, eight of the twenty WBGen fellows that graduated program were recruited from the ECE department undergraduate cohort. The traineeship emphasized as well, from its beginning, the partnership with industry and national laboratories, which took advantage of the successful industry consortium at CPES that has historically been formed by 80–90 power and energy companies working in close collaboration with the center. This gave WBGen fellows the accessibility and possibility to conduct internships at partner facilities during the summer months, focused solely on the evaluation, testing, and adoption of WBG devices, which were many times tightly related to their respective research work and plans. In addition, WBGen fellows conducted their main research work within the confines of research programs at CPES conducted with these industry partners, providing them with a unique opportunity to develop not just their technical expertise—while advancing their knowledge, but to also learn and practice a slew of skills needed for their professional growth. As such, the fellows tackled a variety of WBG-related research topics, from device reliability and capability aspects as well as packaging and integration, encompassing the use of advanced materials and new structures, current sharing challenges, and insulation systems, to advanced gate-drivers with integrated sensors and protection mechanisms and active current- and voltage-based control, to optimized layouts seeking to maximize the switching and power processing performance of these devices, to power processing solutions adopting Gallium-Nitride (GaN) and Silicon-Carbide (SiC) power semiconductors for a variety of applications; including radiation-hardened converters for space dc distribution systems, direct three-phase ac-to-ac power converters for aerospace systems, dc-ac inverters for automotive traction drives, high-frequency isolated dc-dc battery chargers also for heavy transportation systems, and medium-voltage dc-dc and dc-ac converters for distribution systems and future power grids. The WBGen program ultimately graduated a total of 20 power engineers, all experts on WBG-based power electronics, awarding 18 M.S. and 2 PhD degrees in the process. These fellows, all U.S. citizens, allowed CPES to increase the number of citizens students to 33 % at the peak of the program, as the traineeship made possible the recruitment of talent with more attractive graduate research assistantship (GRA) contracts. Unfortunately, the present U.S. citizen enrollment at CPES has declined back to historic levels—approximately 10 %, as the regular GRA rates are not competitive enough when compared with entry-level industry jobs. In all, WBGen fellows published a total of 7 peer-reviewed journal articles, 44 papers at international technical conferences, made 42 presentations at international technical conferences, and filed 4 invention disclosures and patent applications, which have since then been granted by the U.S. Patent and Trademark Office (USPTO). Their contribution to CPES, Virginia Tech, the United States, and the world, has been significant, and continues to yield results thanks to the exemplary career that the fellows have initiated at many of the partners of the program, which include Wolfspeed, Raytheon Technologies, Infineon, Lockheed Martin, Dominion Energy, Northrop Grumman, Rivian, Aerospace Corporation, Sandia National Laboratory, National Renewable Energy Laboratory, John Hopkins University, and Virginia Tech.

14 SOLAR ENERGY↗
DOE OSTI2021

Opportunities for Industry to Provide Flexibility While Increasing Profitability

Supply and demand flexibility will both be needed to ensure the electricity system functions properly as the share from variable renewable generation continues to grow. Industrial manufacturing currently consumes about a third of primary energy worldwide, and electricity is projected to supply an increasing share of this demand as the global economy decarbonizes. Therefore, the ability for industry to flex demand poses an enticing opportunity to enable grid flexibility. However, large capital outlays prevent industry from voluntarily altering demand. Here we show that as battery costs continue to fall, industry will soon be able to profitably alter demand in accordance with electricity price variations. Focusing on two established industries– chlor-alkali and electric arc furnaces – and two industries with large future potential – methane pyrolysis and atmospheric CO 2 capture, we use a linear program (LP) optimization to assess the technoeconomic feasibility of flexible industrial demand across both historical and future-looking wholesale day-ahead marginal prices for the Electricity Reliability Council of Texas (ERCOT). We find positive net present values (NPV) from $\$$400K to $\$$50M using projected 2050 battery prices for industrial purchase of behind-the-meter batteries, using only arbitrage as a source of value. These results indicate that, with projected battery prices, profit-seeking industrial players could voluntarily play a future role in stabilizing a high-renewables grid where electricity prices act as accurate signals of grid needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Battery and backup generator sizing for a resilient microgrid under stochastic extreme events

Owing to the recent power outages caused by extreme events, installing battery energy storage and backup generators is important to improve resiliency for a grid-tied microgrid. In the design stage, the event occurrence time and duration, which are highly uncertain and cannot be effectively predicted, may affect the needed battery and backup generator capacity but are usually assumed to be pre-determined in utility planning tools. This study investigates the optimal battery and backup generator sizing problem considering the stochastic event occurrence time and duration for the grid-tied microgrid under islanded operation. The reliability requirement is quantified by the mean value of the critical customer interruption time in each stochastic islanding time window (ITW), whose length is the duration and the centre is the occurrence time. The stochastic ITW constraint is then transformed to a probability-weighted expression to derive an equivalent Mixed Integer Linear Programming model. Numerical simulations on a realistic grid-tied PV-based microgrid demonstrate that the total cost is reduced by 11.5% considering the stochastic ITW, compared with the deterministic ITW under the same reliability requirement.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Improving Resiliency in Planning MW-Scale Medium and Heavy Duty EV Charging Stations Considering TSCOTS Optimization

Electrification of heavy-duty (HD) vehicles marks an important milestone and technical challenge in the electric vehicle (EV) industry and the public grid. However, implementing EV charging at this scale will necessitate that traditional truck stops be updated with EV charging infrastructure that could represent 10's of MW in electricity consumption. Furthermore, as the transportation sector is represented as critical infrastructure, supporting resiliency considerations in EV charging infrastructure will be critical. This paper proposes an optimization-based approach for optimally designing a MW-scale microgrid charging network. This approach transforms conventional designed truck stops into a reliable HDEV charging stations capable of overnight slow charging and 30-minute to 1 hour fast charging. Using a mixed-integer linear program formulation blending capacity planning and reliability constraints, an optimal network configuration can be solved for a proposed EV charging station that includes photovoltaic and battery energy storage capabilities.

Ponce, Moises [University of Tennessee, Knoxville ↗
DOE OSTI2024

DEPLOYING FAST CHARGING INFRASTRUCTURE FOR ELECTRIC VEHICLES IN URBAN NETWORKS: AN ACTIVITY-BASED APPROACH

This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users' daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charge (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. The problem of finding the optimum charging configuration is then formulated as a mixed-integer nonlinear programming problem that considers the dynamics of travel time and travel distance, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.

Chain of Trips↗