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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

ARPA-E: Celebrating the Energy Entrepreneur

The world faces urgent energy challenges brought on by projected population increases, aging infrastructure and the global threat of climate change. ARPA-E is investing in some of the country’s brightest energy entrepreneurs that are developing innovative technological options to help meet future energy needs. Featuring remarks from ARPA-E Director Dr. Ellen D. Williams, as well as interviews with the Deputy Director of Commercialization Dave Henshall, Senior Technology-to-Market Advisor Sue Babinec, and a number of ARPA-E awardees, this video highlights the energy entrepreneur, and the critical role they play in creating solutions to address future energy challenges and ensure a secure energy future. The video also incorporates footage shot on site with several ARPA-E awardees who are spurring innovation, much of which will be highlighted in other videos shown throughout the Summit.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Progress & Frontiers in PV Performance

PowerPoint slides for a presentation given at Solar Power International 2016. Presentation includes System Advisor Model (SAM) introduction and battery modeling, bifacial PV modules and modeling, shade modeling and module level power electronics (MLPE), degradation rates, and PVWatts updates and validation.

14 SOLAR ENERGY↗
DOE OSTI2016

University-level Non-proliferation and Safeguards Education and Human Capital Development Activities at Brookhaven National Laboratory

BNL has offered Nuclear Nonproliferation, Safeguards and Security in the 21st Century,? referred to as NNSS, every year since 2009 for graduate students in technical and policy fields related to nuclear safeguards and nonproliferation. The course focuses on relevant policy issues, in addition to technical components, and is part of a larger NGSI short course initiative that includes separate courses that are delivered at three other national laboratories and NNSA headquarters. [SCHOLZ and ROSENTHAL] The course includes lectures from esteemed nonproliferation experts, tours of various BNL facilities and laboratories, and in-field and table-top exercises on both technical and policy subjects. Topics include the history of the Treaty on the Non-proliferation of Nuclear Weapons (NPT) and other relevant treaties, the history of and advances in international nuclear safeguards, current relevant political situations in countries such as Iran, Iraq, and the Democratic Peoples? Republic of Korea (DPRK), nuclear science and technology, instrumentation and techniques used for verification activities, and associated research and development. The students conduct a mock Design Information Verification (DIV) at BNL?s decommissioned Medical Research Reactor. The capstone of the course includes a series of student presentations in which students act as policy advisors and provide recommendations in response to scenarios involving a current nonproliferation related event that are prepared by the course organizers. ?The course is open to domestic and foreign students, and caters to students in, entering, or recently having completed graduate school. Interested students must complete an application and provide a resume and a statement describing their interest in the course. Eighteen to 22 students attend annually; 165 students have completed the course to date. A stipend helps to defray students? travel and subsistence expenses. In 2015, the course was shortened from three weeks to two weeks to streamline the material, standardize NGSI course length, and draw in a larger applicant pool. ?The international and interdisciplinary mix of students attending the course encourages discussions of the topics presented during the course. Information about the course is available at https://www.bnl.gov/nnsscourse/. While a complete analysis of course students has not been undertaken, BNL is aware of three individuals who worked at national laboratories after attending the NNSS course, one who worked at a national laboratory prior to attending NNSS, two who worked as federal employees after attending NNSS, three who were Nonproliferation Graduate Fellows before or after attending NNSS, and three who have participated in other NGSI activities.?Design Information Verification is an IAEA inspection activity that is implemented for the purpose of ensuring that the facility design is consistent with the declared use of a facility.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

ARPA-E: Actively Managing Projects to Accelerate Impact

The ARPA-E model is unique in that the agency does not just provide teams funding. Throughout the lifetime of an ARPA-E award, ARPA-E Program Directors and Tech-to-Market Advisors also provide teams with expert advice through quarterly reviews and onsite visits. This hands-on approach helps ensure teams can meet ambitious milestones, target and tackle problems early on, and advance their technologies towards commercialization. Program Director Dr. Isik Kizilyalli explains the importance of this active project management approach in helping teams identify and overcome barriers. In this video, Energy Storage Systems (ESS) from the GRIDS program and Monolith Semiconductors from the SWITCHES program discuss how ARPA-E’s active project management approach helped them find solutions to technical challenges.

25 ENERGY STORAGE↗
DOE OSTI2016

LK Scripting Language

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Version 3.0+ toolkit.

Source record↗
DOE OSTI2018

2018 Research Highlight in Manufacturing: Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

Currently, geothermal project developers customize the size of the power plant to fit the resource being developed. The turbine is designed and sized to optimize efficiency and resource utilization for electricity production; most often, other power plant components are then chosen to complement the turbine design. These custom turbine designs demand one-off manufacturing processes, which result in higher manufacturing setup costs, longer lead-times, and higher capital costs overall in comparison to larger-volume line manufacturing processes. In contrast, turbines produced in standard increments, manufactured in larger volumes, could result in lower costs per turbine. In this study, we developed a manufacturing cost model to identify requirements for equipment, facilities, raw materials, and labor. Then we used discounted cash flow (DCF) analysis to calculate the minimum sustainable price (MSP). We analyzed three different cases 1) 1 MWe geothermal ORC turboexpander 2) 5 MWe ORC turboexpander and 3) 20 MWe geothermal steam turbine, and calculated the cost of manufacturing the major components, such as the impellers/blades, shaft/rotor, nozzles, inlet guide lanes, disks, and casings. The results showed that MSP could highly vary between 893 $/kW and 30 $/kW based on turbine size, standardization and volume of manufacturing. The analysis also showed that the economy of scale applies both to the size of the turbine and the number manufactured in a single run. As an example, the unit price of a 5 MW standard design turbine could be 150 $/W cheaper than the custom design. Sensitivity analysis indicated that these savings come largely from reduced labor costs for design and engineering and manufacturing setup. In addition to manufacturing cost savings, there is a delivery time saving up to 10 months, which could have a positive effect to construction financing operation time. Another advantage of these standard turbines is their adaptability to different geothermal systems by operating at off-design conditions. We also modeled off-design turbine efficiencies within the commercially-favorable operating range of a standard ORC compared to custom-designed ORC equipment. Than we used these performance calculations and power output capacities in a discounted cash flow (DCF) analysis of plant operations and financing, thereby creating representative techno economic models of a total geothermal power plant. I this scope we used NREL's System Advisor model (SAM) and performed DCF analysis of standard and custom design turbines using results from IPSEpro over range of temperatures of interest. In this scope 63 different off-design cases were analyzed. This helped us to answer the question; 'Can today`s capital cost savings compensate the future revenue losses due to lower electricity generation?' The results showed that, the net capital cost savings for the modeled 5 MW case study may reach up to +$1,298,672. Also, the difference between NPV of standard design and custom design turbine could reach up to +$733,940. To sum up, when all the things mentioned above are taken into consideration, it can be said that, the standard turbines are competitive over a wide range of temperatures and flow rates and the give positive NPV differences for certain cases near their design point.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Behind-the-Meter Solar + Storage Modeling Tool Comparison

Several techno-economic models exist to evaluate solar PV plus battery storage opportunities for behind-the-meter, commercial application. This tool comparison evaluates the methodological differences between several solar plus storage modeling tools and employs a case study to compare their outputs. The tools selected for comparison include NREL's REopt Lite, NREL's System Advisor Model (SAM), Homer Energy's Homer Grid, Geli ESyst, EPRI StorageVET, and LBL's DER-CAM. The comparison focuses on each tool's simulation and optimization capabilities, PV and battery performance modeling, dispatch strategies, and economic model assumptions and calculations, with brief mention of additional capabilities outside the scope of behind-the-meter PV and battery storage. This report describes the case study's tool inputs and outputs and dives into the differences in assumptions, methodologies, and capabilities between tools.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Hybrid Systems to Enable High Penetration PV

A model for PV plus energy storage and fuel cells was developed in the System Advisor Model (SAM). This model was used to evaluate the ramp rate and interconnection capacity factor for a hypothetical utility-scale plant for several configuration options. For PV only, the plant experienced 3345 violations of a 10%/minute ramp up limitation and a interconnection capacity factor of 17.6%. Adding a battery reduced the violations to 154 per year and the magnitude of the average violation to 2%. Adding a fuel cell to the PV system increased the capacity factor to 78% without improving ramp violations. Using a combined PV plus storage plus fuel cell arrangement maintained the improved capacity factor while reducing ramp up violations to 23, illustrating the potential to operate a hybrid system both to enable grid integration requirements and increase utilization of the interconnection.

14 SOLAR ENERGY↗
DOE OSTI2019

Hybrid Systems to Enable High Penetration PV: Preprint

A model for PV plus energy storage and fuel cells was developed in the System Advisor Model (SAM). This model was used to evaluate the ramp rate and interconnection capacity factor for a hypothetical utility-scale plant for several configuration options. For PV only, the plant experienced 3345 violations of a 10%/minute ramp up limitation and a interconnection capacity factor of 17.6%. Adding a battery reduced the violations to 154 per year and the magnitude of the average violation to 2%. Adding a fuel cell to the PV system increased the capacity factor to 78% without improving ramp violations. Using a combined PV plus storage plus fuel cell arrangement maintained the improved capacity factor while reducing ramp up violations to 23, illustrating the potential to operate a hybrid system both to enable grid integration requirements and increase utilization of the interconnection.

14 SOLAR ENERGY↗
DOE OSTI2019

DE-SC0016684 - DOE Final Scientific and Technical Report

The Computing Research Association’s Committee on the Status of Women in Computing Research (CRA-W) aims to increase the number of women who participate and succeed in computer science research at every stage of the research pipeline. Achieving these objectives requires that an increasing number of women start and progress to the next stage. The CRA-W Grad Cohort Workshop is focused at the graduate level to maximize the likelihood participants will successfully complete their graduate degrees. Factors such as role models, skills, competence, confidence, mentoring, social support, and development of identity as a researcher help students to persist in graduate school, while factors such as sexism, racism, and dissatisfaction with their graduate program may cause them to leave. We, therefore, help first, second, and third year students build their skills, research strategies, and confidence; meet potential mentors from outside their institutions; develop connections with each other and with their research communities; and inform them about strategies for successful publishing, speaking, and advisor management strategies. By targeting early graduate students, we seek to help them stay in graduate school and in research.

Russell, Erik↗
DOE OSTI2019

DC-Connected Solar Plus Storage Modeling for Behind-the-Meter Systems in SAM

A detailed model for PV plus DC-connected batteries was developed. This model was compared to an existing AC connected battery model in the System Advisor Model (SAM) tool using a hypothetical Honolulu residence with a PV plus storage system. The stand-alone PV system was shown to provide the most value; however due to the increased difficulty of PV systems being approved for grid interconnection in Hawaii, it is valuable to install an AC or DC connected battery to enable full PV self-consumption under a less restrictive interconnection option. In that case both battery systems enabled full PV self consumption at the residence, requiring no power to be exported to the grid. The DC-connected battery system captured energy from the PV array which would have also been clipped due to inverter limitations. For a PV system with DC/AC ratio of 1.23, the battery configurations produced net-present values within 1% of each other, but when the DC/AC ratio increased to 1.85, the DC-connected system increased the net-present value by 13%.

14 SOLAR ENERGY↗
DOE OSTI2019

Method and System for Accessing PV Resource Data from the NSRDB: Preprint

This study developed a capability to provide spectrally resolved solar resource data from the National Solar Radiation Database (NSRDB), effectively providing 20 years of half-hourly data for all of the United States at a 4-km by 4-km spatial resolution. These data are now available freely to users directly through a geographic information system-based web interface (https://nsrdb.nrel.gov) as well as through an application programming interface. Users of these data can conduct more accurate prefeasibility studies and assess multiple photovoltaic (PV) technologies. It is expected that widely used models such as PVSyst, the National Renewable Energy Laboratory's System Advisor Model (SAM), and First Solar-designed PlantPredict will develop the capabilities to use these spectral data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

EFRC 10@10: Developing the Next Generation of Scientific Talent: Michael Naguib

This is a biography of Michael Naguib, winner of the Workforce Development Award at the EFRC 10@10 Awards Ceremony in 2019. Michael Naguib was born in Egypt and completed his undergraduate and master’s degrees at Cairo University. He wanted to study advanced materials, but there was no place to do so in Egypt. Instead he enrolled in a PhD program at Drexel University in Philadelphia. There he was assigned to explore whether certain materials that have a layered structure (with three layers, each having a different chemical composition) could be used to make better electrodes for lithium ion batteries. Michael found that the materials were not useful as electrodes because lithium ions (the charge carriers in modern batteries) could not penetrate the material. To address this, he tried to modify the material by removing the middle layer with acid. The unexpected result was the discovery of a completely new nano-material: a titanium-carbon compound in the form of a two-dimensional sheet less than a nanometer thick. He and his advisors at Drexel immediately recognized the new material’s potential for energy storage. Publication of that discovery—of what soon became clear was a whole family of two-dimensional materials now called MXenes—triggered a world-wide surge of research. To explore MXenes and related phenomena in more detail, the U.S. Department of Energy’s Office of Science funded an Energy Frontier Research Center (EFRC) on Fluid Interface Reactions, Structures and Transport. The research team included computational modelers, university experts in materials synthesis and thermodynamic analysis, and scientists at DOE’s Oak Ridge National Laboratory (ORNL) who could probe the material’s structure with neutrons and powerful microscopes.

25 ENERGY STORAGE↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Demonstrating SolarPILOT's Python API Through Heliostat Optimal Aimpoint Strategy Use Case: Preprint

SolarPILOT is a software package that generates heliostat field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL's System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application's graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called "LK." This paper presents a new, full-featured Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT's capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instances with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layout; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying heliostat field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating heliostat field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed tower CSP analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot's functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize CSP tower research.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Powering the Blue Economy: Economics of Marine Renewable Energy Systems

This presentation, part of the Policy and Innovation Drivers Shaping the Market for Marine Renewable Energy panel of the 2020 Marine Renewable Energy Conference: On and Off the Grid, moderated by Leslie-Ann McGee, Assistant Director of the Consortium for Marine Robotics at the Woods Hole Oceanographic Institution and Program Manager, Cape Cod Blue Economy Foundation, delves into government policies incentivizing technological advances, collaborative models for technology development, market trends, and permitting hurdles. Panelists include: Jennifer Garson, Senior Advisor, U.S. Dept. of Energy Lead for the Powering the Blue Economy Initiative; Henry Jeffrey, Chairman of the Technology Collaboration Programme for Ocean Energy Systems, University of Edinburgh; Alf Carroll, SBIR Blackbelt and Ocean Energy SME, Raytheon Technologies; Walter Schurtenberger, Founder, Hydrokinetic Energy Corp.; and Dale "Scott" Jenne, Engineer, National Renewable Energy Laboratory.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

A Case Study of LLVM-Based Analysis for Optimizing SIMD Code Generation

This paper presents a methodology for using LLVM-based tools to tune the DCA++ (dynamical cluster approximation) application that targets the new ARM A64FX processor. The goal is to describe the changes required for the new architecture and generate efficient single instruction/multiple data (SIMD) instructions that target the new Scalable Vector Extension instruction set. During manual tuning, the authors used the LLVM tools to improve code parallelization by using OpenMP SIMD, refactored the code and applied transformation that enabled SIMD optimizations, and ensured that the correct libraries were used to achieve optimal performance. By applying these code changes, code speed was increased by 1.98× and 78 GFlops were achieved on the A64FX processor. The authors aim to automatize parts of the efforts in the OpenMP Advisor tool, which is built on top of existing and newly introduced LLVM tooling.

Huber, Joseph↗