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At least 55 records · Page 3

NREL ASSIST Rhode Island / Thermodynamic retrievals TROPoe

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous observations from the NREL ASSIST-II (SN 11) infrared spectrometer. Observations are noise-filtered but not averaged in time to minimize errors due to non-uniform clouds. Additional input data in TROPoe are cloud base height from a collocated NREL Upgraded Galion lidar #1212-60 and temperature, RH, and pressure from collocated PNNL met station. The lidar beta is used to estimate the cloud base height through a modified algorithm by Newsom et al., 2019 used at ARM SGP. The full pipeline for running the retrieval is available at https://github.com/StefanoWind/TROPoe_processor. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) which provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see e.g. Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗

NREL's International Programs: Highlights

This fact sheet provides an overview of four international projects at NREL: the Net Zero World Initiative, the Global Climate Action Partnership (GCAP), the USAID-NREL Partnership, and the Global Power System Transformation Consortium (G-PST).

ENERGY PLANNING, POLICY, AND ECONOMY,ENVIRONMENTAL↗

NREL’s Wind Turbine Drivetrain Condition Monitoring and Wind Plant Operation and Maintenance Research During the 2010s: A US Land-Based Perspective

The wind industry has seen tremendous growth during the past two decades, with the global cumulative installation capacity reaching more than 650 gigawatts by the end of 2019. Despite performance and reliability improvements of utility-scale wind turbines over the years, the industry still experiences premature component failures, leading to increased operation and maintenance (O&M) costs. Among various turbine components, gearboxes—and, more broadly, drivetrains—have shown to be costly to maintain throughout the design life of a wind turbine. The problem of premature component failure is industry wide. As early as 2007, the US Department of Energy (DOE) started to address this challenge through the National Renewable Energy Laboratory’s (NREL’s) reliability initiative that first focused on gearboxes and more recently expanded to entire drivetrains. The wind turbine drivetrain condition monitoring and wind plant O&M research that is the subject of this paper is part of the NREL initiative and includes a few research and development (R&D) activities conducted during the 2010s. These activities included technology evaluation during the first few years; novel monitoring technique investigation (specifically, compact filter analysis) during the middle years; and data and physics domain modeling for fault detection and prediction in recent years. A high-level summary of these activities is provided in this paper along with some key observations from each activity. Most of the work discussed has been published and can be referred to for more information. They reflect the expected evolution of wind turbine condition monitoring and O&M in the US market—primarily, a land-based perspective. In addition, we have identified several R&D opportunities that can be picked up by the research community to help industry advance in related areas, making wind power more cost competitive in the future.

17 WIND ENERGY↗

Accurate Efficiency Measurements for Emerging PV: A Comparison of NREL's Steady-State Performance Calibration Protocol Between Conventional and Emerging PV Technologies

Emerging PV technologies (e.g. Perovskite, and Quantum Dot) are commonly known to possess challenges for accurate performance measurement under the existing IEC 60904 series of standards, which were developed for conventional Si solar cells. Potential performance artifacts depending on scan rates and directions and light bias exposure history are often seen in those emerging solar cells. To avoid these artifacts and provide an unbiased and reliable efficiency measurement, NREL's Cell and Module Performance (CMP) Group has developed a steady-state performance calibration protocol - the asymptotic P MAX method. In this paper, we applied this procedure to four PV cell technologies, Si, CIGS, perovskite, and Quantum Dot (QD), and compared their performance variations between the transient and the steady-state conditions. By comparison, we found that the performance parameters ( i.e. V OC , I SC , FF, ..eta..) measured between fast I-V scans (and the asymptotic method (steady-state) change significantly for perovskite and QD cells. These changes do not happen for Si and CIGS cells. Furthermore, the statistical performance analysis on nearly 100 emerging cells received globally (including OPV, Perovskite, and QD) shows that over 70 % of the fast I-V scans have a relative performance deviation larger than 1% compared to those determined using the asymptotic P MAX scan. Given the complex dynamic behavior observed in emerging PV devices, the CMP group at NREL thus only certifies their steady steady-state performance using the Asymptotic P MAX method. We highly recommend similar steady-state performance calibration protocol for all researchers in emerging PV because accuracy in reported efficiencies is critical to the long-term success of those promising new PV technologies.

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

NREL's Improved Linearity Testing of Photovoltaic Reference Cells

Photovoltaic devices are characterized under standard testing conditions that include a defined reference spectrum and total irradiance. International standards for reference cell calibrations require that reported reference cell response (typically Isc) vs. total irradiance must be linear. How can linearity be efficiently determined? In 2006 NREL developed a test bed, based on the "two-lamp method" that provided a low cost, but low accuracy method for determining whether cell response was linear with irradiance. This paper describes very simple changes to NREL's historical method [1] for determining linearity that yield greatly improved results. It also describes a method that can be used to quantify and correct for non-linearity.

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

NRWAL (NLR formerly known as NREL Wind Analysis Library) [SWR-21-26]

NRWAL (NLR (National Laboratory of the Rockies) formerly known as NREL (National Renewable Energy Laboratory) Wind Analysis Library: A library of offshore wind cost equations (plus new energy technologies like marine hydro!) Easy equation manipulation without editing source code Full continental-scale integration with the NREL Renewable Energy Potential Model (reV) https://nrel.github.io/reV/ Ready-to-use configs for basic users Dynamic python tools for intuitive equation handling One seriously badass sea unicorn To get started with NRWAL, check out the NRWAL Config documentation or the NRWAL example notebook. You can also launch the notebook in an interactive jupyter shell right in your browser without any downloads or software using binder. Ready to build a model with NRWAL but don't want to contribute to the library? No problem! Check out the example getting started project here. Here is the important stuff: The NRWAL Equation Library. Default NRWAL Configs

Nunemaker, Jacob↗

Case Study: NREL Campus Chilled Water Storage Potential: Benchmark Datasets Development and Applications, Task 4 - Use Case Demonstration

The Benchmark Datasets Development and Applications project is a three-year collaboration between the National Renewable Energy Laboratory (NREL), Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory. The project seeks to collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms. Project outcomes include approximately twelve high-fidelity building datasets, enhanced data representation tools, and four case studies to illustrate example applications. The goal of these case studies is to define and execute analyses that demonstrate how one or more datasets collected through this project can address a data gap or challenge historically faced by building stakeholders. This technical paper summarizes the findings of one of these case studies, in which we studied the operational efficiencies of the central cooling system at NREL. We looked at three years of data from the three chillers in the Field Test Laboratory Building (FTLB), from 2019 to 2021, to compare equipment operation and demand throughout the time period. Our analysis indicates that all three chillers are operating at or below the optimal loading conditions for most of the operation time, and thus there was no efficiency drop due to loading of the chillers at full capacity. Our recommendation is that no chiller capacity increase is needed; instead, the central plant could benefit from adopting advanced control logics for optimal sequencing of chillers during part load operations. Analysis of adding chilled water thermal storage to the central plant indicated 34% savings in demand cost and 24.5% savings in total cost (energy consumption and demand charge cost). The payback period is estimated to be 11-22 years with an assumed TES cost of $\$$100-$200 per ton. This case study shows how a selected dataset is used to solve a practical building problem - learning the operational status of its components, analyzing the effectiveness of a proposed new technique, and aiding decision-making for the building operations and maintenance team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Clear-Sky Probability for the 2023 Annular Solar Eclipse and the 2024 Total Solar Eclipse Using the NREL National Solar Radiation Database

The National Renewable Energy Laboratory (NREL) and collaborators have created a clear-sky probability analysis to help guide viewers to the 2023 annular solar eclipse and the 2024 total solar eclipse. Using cloud and solar data from the NREL National Solar Radiation Database (NSRDB), the analysis provides cloudless-sky probabilities specific to the date, time, and location of each eclipse with a 4-km resolution. Though not intended to be an eclipse weather forecast, the detailed maps can help guide eclipse enthusiasts to likely optimal viewing locations. Additionally, high-resolution data are presented for the centerline of the path of each eclipse, representing the likelihood for cloudless skies and atmospheric clarity. The NSRDB provides industry, academia, and other stakeholders with high-resolution solar irradiance data to support feasibility analyses for photovoltaic and concentrating solar power generation projects.

14 SOLAR ENERGY↗

Representation of Fossil Power Generation Technologies in NREL’s Annual Technology Baseline

This presentation was delivered at the Energy Economics USAEE/IAEE North American Conference on November 7, 2023. The presentation highlights support provided by the National Energy Technology Laboratory (NETL) on the development of National Renewable Energy Laboratory's (NREL) Annual Technology Baseline (ATB). The ATB documents transparent, normalized technology cost and performance assumptions using public sources. NETL's role in the development was to provide NREL with performance and cost data for select fossil-based technology classes. The ATB was released in June 2023.

Hackett, Gregory↗

Illuminating Agrivoltaics at NREL

In this talk, we will provide an overview of the INSPIREing work being done in the agrivoltaics field at NREL. We will focus on the modeling aspects of agrivoltaics, discussing key assumptions and metrics that guide research, and main open concerns from the community. We will innovative solutions implement at NREL for modeling, and ongoing experiments for shading and irradiance modeling. We will conclude with a look at the future steps necessary to advance this particular area of agrivoltaics.

14 SOLAR ENERGY↗

NREL Infrastructure Perception and Control Workshop

A lack of highly reliable, full state-space awareness of roadway situations is the current bottleneck for the incremental introduction of smart infrastructure control. NREL's Infrastructure Perception and Control (IPC) lab applies advanced sensing and computation controls to the coordinated movement of vehicles on the road as well as people in large facilities and has produced field test results from a Colorado Springs intersection. In this presentation, NREL discusses the state of smart infrastructure control and opportunities for partnership.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗

NREL Tools Webinar Series: Session 1 - Overview

Webinar with NARC/Solsmart to showcase NREL tools related to energy with local governments interested in Solsmart designation. NREL staff will present on SAM, PV Watts, REopt, Procurement Analysis Tool, Slope, SolarAPP+, and SolarTRACE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

V2G AC Standards Support at NREL

This slide deck will guide participants through the landscape of V2G AC standards, development statuses of them, and explain the support of NREL and NREL's evaluation plans that leverage the real hardware and solution offered by private industry. This slide deck will be presented during a panel session that "will examine the readiness of North American V2G AC standards for broader market deployment, contrasting it with behind-the-meter applications such as vehicle-to-home. Panelists will address status of the V2G-AC standards for North America including UL 1741 SC, SAE J3072, ISO 15118-20 Am 1 and the new UL 1741 SB CRD. With V2G-AC momentum building, this session offers a timely opportunity for the industry to engage in candid dialogue on the progress of standardizing V2G AC in the evolving energy and mobility landscape."

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The NREL Sensor Laboratory Detection of Hydrogen Emissions

The development of a functional hydrogen detection system is a multifaceted process that integrates hardware, deployments strategies, and analytics which can be supported by the NREL Sensor Laboratory: 1. Support of the design, validation and optimization of sensing prototypes; 2. Guide optimized sensing element development, including control electronics; 3. Laboratory testing to validate/optimize metrological performance (measurement range, detection limit, etc.); 4. Provide test sites for field deployments representative of real-world scenarios with controlled hydrogen releases; 5. Develop sensor placement and operation guidance; 6. Provide guidance on electronics to accommodate facility integration; 7. Electrical safety designs to allow for operation within restricted zones; 8. Integration into facility monitoring and control systems; 9. Guide incorporation of cyber security elements to protect facilities from malicious attacks; 10. Modeling and application of advanced analytics to detect and quantify emissions; 11. Higher Order dispersion models to guide sensor placement for reliable detection; 12. Advanced analytics for improved metrological performances, and to inform inverse modeling; 13. Market support and commercialization (national and international markets); 14. Commercial deployments in H2@SCALE markets (e.g., HUBs and other large-scale hydrogen markets); and 15. Leverage off international collaborations/partnerships (e.g., NREL is on the advisory board for the European initiative "pre-Normative Research on Hydrogen Releases Assessment"-NHyRA).

08 HYDROGEN↗

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↗

Hydrogen R&D at NREL

This presentation provides an overview of the hydrogen R&D activities at NREL, including make, store, move, and use hydrogen. At NREL, our research spans the advanced water splitting materials (AWSM) and hydrogen storage R&D, performed within the HydroGEN and HyMARC Energy Materials Networks (EMN), respectively, to the materials integration and scale up work done within the H2NEW consortium, to fuel cell R&D within the M2FCT consortium, to stack and systems testing at the MW-level. These R&D activities are funded by U.S. Department of Energy Hydrogen and Fuel Cell Technologies Office.

08 HYDROGEN↗