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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Impacts of Variable Renewable Energy on Bulk Power System Assets, Pricing, and Costs

We synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted to date or might in the future impact bulk power system assets, pricing, and costs. We do not analyze impacts on specific power plants, instead focusing on national and regional system-level trends. The issues addressed are highly context dependent—affected by the underlying generation mix of the system, the amount of wind and solar penetration, and the design and structure of the bulk power system in each region. Moreover, analyzing the impacts of VRE on the bulk power system is a complex area of research and there is much more to be done to increase understanding of how VRE impacts the dynamics of current and future electricity markets. While more analysis is warranted, including additional location-specific assessments, several high-level findings emerge from this synthesis: -VRE Is Already Impacting the Bulk Power Market -VRE Impacts on Average Wholesale Prices Have Been Modest -VRE Impacts on Power Plant Retirements Have So Far Been Limited -VRE Impacts on the Bulk Power Market will Grow with Penetration -The ’System Value’ of VRE will Decline with Penetration -Power System Flexibility Can Reduce the Rate of VRE Value Decline All generation types are unique in some respect—bringing benefits and challenges to the power system—and wholesale markets, industry investments, and operational procedures have evolved over time to manage the characteristics of a changing generation fleet. With increased VRE penetrations, power system planners, operators, regulators, and policymakers will continue to be challenged to develop methods to smoothly and cost-effectively manage the reliable integration of these new and growing sources of electricity supply.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Existing Hydropower Assets (EHA) Capacity Factor Plant Database, 2005-2024

Existing Hydropower Asset (EHA) Annual Capacity Factor is a geospatial point-level dataset containing annual capacity factors over the years (2005-2024) and key characteristics of operational U.S. hydropower plants with 1 megawatt or greater of nameplate capacity. EIA form 860 and EHA are the primary sources of the derived data. Pumped storage and hybrid plants are excluded.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗
DOE OSTI2020

Challenges and Opportunities in Turning Large U.S. Archives of Analog Seismograms into a Modern Usable Resource

Abstract Quantitative seismology is based firmly on the analysis of actual ground motions, and the transition to digital recording in the 1980s enabled sophisticated new capabilities to extract useful results from waveforms. With some effort, these tools can also be applied to analog records. Focusing on assets available within U.S. institutions, we review the necessary steps and the challenges in enabling “data rescue”—that is, preserving the scientific information latent in large analog seismogram archives and making it usable. They include: determining what assets are available (the analog seismogram archives held by various institutions, with associated metadata on instrument responses, station locations, and timing information); developing a consensus on the top level of a triage process (which analog records most definitely should be rescued?); deciding the level of quality needed in copying original seismograms to media suitable for digitizing; assessing the relative merits of scanning and digitizing; and, the need for a community service in distributing scans and digital records, as they accumulate. The necessary level of effort can benefit from practical experience. For example, specific studies have used digitized versions of analog recordings to model earthquake sources and assess seismic hazard. Other studies have used them to gain experience with nuclear explosion signals recorded at regional distances, noting that regional signals enable explosions to be monitored down to levels much lower than those attainable teleseismically. The opportunities presented by large archives of analog seismograms include the insights they present to current and future seismologists studying earthquakes and explosions, into the practical areas of assessing seismic hazard, monitoring for test ban compliance down to low explosion yields—and prompt characterization of actual explosions should they occur, as well the traditional academic pursuit of a better understanding of earthquake physics.

Geochemistry & Geophysics↗
NASA NTRS2021

Dare Mighty Things

Winston Churchill once said, “To improve is to change; to be perfect is to change often.” JPL’s Property Accountability objective is to provide superior services related to property accountability, reutilization, and disposition. JPL must report property reutilized and disposed through either sales, donation, or scrap. Implementing the JPL designed and built Property Information Reporting System (PIRS), opened a new perspective with our data and what are we reporting to NASA. With this new depth of visibility, we self-implemented as assessment to validate the fiduciary and stewardship responsibilities of what is being reporting to NASA. JPL strives to perform at a level beyond the basic primary expectations of our NASA requirements. JPL developed the PIRS - which rolled out in 2018 - to simplify the delivery of JPL’s Personal Property and Equipment (PP&E) reporting: PIRS takes the raw data from Oracle to generate the NASA Form (NF) 1018 and Contractor Held Asset Reporting System (CHATS) Reports, and to meet the requirements established for AS9100 compliance. The data presented from PIRS is exportable and used to analyze our property records. JPL is also embarking on an effort to define the JPL of the future with “Enterprise 2.0”. Enterprise 2.0 is the driving force of JPL’s strategy to digitally transform the Laboratory from the current legacy processes and systems to a modern, integrated, information-driven highway of business transactions. This should include automation of routine processes and data-related tasks, integration of data and systems, advanced search and analytics, and improved information sharing and collaboration. As JPL’s evolving landscape of digital technologies advance to meet the future, JPL Property Accountability is making strides to surpass these expectations. For every cause there is an effect: a revealing of something that aids in the further development and transformation of JPL best business practices.

Sucher, Jay M↗
DOE OSTI2021

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report: FY19-FY22)

This is the final technical report for the FY19-FY21 research program "R&D to Ensure a Scientific Basis for Qualification Tests and Standards." This research was performed because project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. This program advances PV module reliability of commercial products through identification of reliability needs, characterization that provides scientific understanding of targeted degradation mechanisms, and translation of those data into practical and predictive test protocols and standards. This report describes program scope, results, milestones, and accomplishments over the three-year period of performance.

14 SOLAR ENERGY↗
NASA NTRS2020

The Biological Potential of Present-day Mars

In the mid-1970s the twin Viking Landers conducted three biological experiments in two different locations on the surface of Mars. Results from these experiments did not provide conclusive evidence of biological activity, and instead they were consistent with abiotic chemical reactions in the regolith. The paradigm established by the Viking missions is that the near-surface environment on Mars is too cold, dry, and hostile for life as we know it. Our understanding of the limits of metabolic activity and growth in terrestrial organisms, together with ecological studies in terrestrial analog environments, some of which approximate the temperature and dryness conditions on Mars, seem to support this view. But data gathered by surface and orbital assets in the past two decades suggests that liquid water could still be an important agent of landscape evolution over timescales ranging from seasons to millions of years. In addition, the tantalizing discovery of both liquid water buried deep beneath the southern polar deposits and fluctuating levels of methane in the atmosphere make the existence of a subsurface biosphere both possible and realistic. These discoveries have sparked a renewed interest on the biological potential of present-day Mars, and the possibility of extant life. This chapter reviews the environmental aspects most relevant to the biological potential of present-day Mars, emphasizing the near-surface environment that will be sampled and investigated by future robotic missions.

Life↗
DOE OSTI2019

INL WTB Overview Capabilities Future v14_040419

INL Wireless Test Bed Mission Provide highly-regarded cellular, wireless and communications technical expertise, systems and environment to enable: Test & Demonstrate full scale wireless systems and equipment With and without controlled interference Terrestrial, Subterranean and Airborne Demonstrate new & emerging wireless technologies Develop and Train to Tactics, Techniques and Procedures (TTPs) for wireless systems In a real world environment and configurations at real frequencies and real power levels to make informed decision State-of-the-Art INL WTB Assets and Capabilities Instrumentation: RF waveform analyzers, generators Protocol analyzers Noise generators for controlled interference Established Services & Processes: Spectrum approval & monitoring Safety, Medical, Fire, Security (physical) Resource management - personnel, networks, configuration control Secure, IP protected multi-user facility Broadband data access – entire INL Range Hardware prototyping, scientific labs Visitor – US citizen & foreign national

2G↗
DOE OSTI2026

Demonstrating the data center as a flexible grid asset using a C-HIL setup

Increasing data center demand is outpacing grid infrastructure development. Artificial intelligence workloads and hyperscale cloud growth are creating unprecedented demand for power, while traditional grid expansion faces multiyear development timelines. Verrus is developing an innovative datacenter solution for this challenge, data centers that act as active grid-supportive assets rather than passive loads. Our approach integrates a novel grid-aware power flow management system with battery energy storage systems(BESS) into a microgrid-controlled, medium-voltage power distribution architecture that delivers critical capabilities, such as: * Fast response to grid disturbances such over/ under voltage or over/ under frequency * Demand flexibility that can service requests from the utility within 10 s * Uninterrupted transition to islanded operation during grid outages * Continuous uptime assurance for compute loads while maintaining all customer service level agreements. Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), these capabilities were validated using NREL's Advanced Research on Integrated Energy Systems (ARIES) virtual emulation environment to model a 70-MW grid-interactive data center. This paper outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can provide both critical load resilience and ancillary grid support without compromising uptime requirements. Specifically, we present a digital real time simulation of a 70 MW data center integrated with a physical microgrid controller, and demonstrate the data center response in the event of a grid voltage and frequency event, utility demand response request and utility outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Igiugig Site Visit Report

The National Renewable Energy Laboratory (NREL) team conducted a site visit during January 23-25, 2019 with the Igiugig Village Council (IVC) and other stakeholders to assist the community of Igiugig in refining their long-term energy strategy. The agenda included a tour of the village, data collection, presentations, long-term visioning exercises, identification of energy scenarios, and a school presentation. Participants in the site visit activities spanned a range of local, regional, government, and industry participation. There were 24 attendees at the all-day community workshop on Thursday, January 24th, with participants from the IVC, NREL, Bristol Bay Native Association (BBNA), Bristol Bay Native Corporation (BBNC), Lake and Peninsula Borough, Alaska Energy Authority, Intergrid, ORPC, Deer Stone Consulting, the Southwest Alaska Municipal Conference, and University of Alaska Fairbanks - Alaska Center for Energy and Power. Igiugig is a well-organized rural Alaskan community, with a leadership team that appears to have broad community support. The use of consensus-based decision making is one tangible example of how the leadership team actively invokes and promotes community-focused thinking. The NREL team observed anecdotal evidence of how this approach seems to be strengthening the community: active participation in the visioning exercise, a student hosted fund-raiser dinner at the school, a clean and organized landfill, and well-maintained roads and buildings. Igiugig has wind, solar, and river hydrokinetic resources readily available within the community. Wind has shown to be a promising resource in the region, and has been integrated into microgrids around the state, but the community has had mixed success with wind technologies: some devices failed quickly and others continue to operate. The economics of solar energy are improving in Alaska, and economical solar projects are being installed around the state. Considering that economic activity in Igiugig peaks during the summer sport fishing season, solar could prove to be a valuable supplement to the electrical system. Igiugig has been a test site for two different river hydrokinetic devices, and they have began a third project to operate ORPC's RivGen device, which is delivering valuable device performance data, operations and maintenance experience, and design refinement information. Already, this device has made over 7-million revolutions, and delivered over 8 MWh of power to the community. Igiugig's river resource is fairly unique because it is available year-round and has the potential to provide reliable base-load power for months at a time. A preliminary investigation of this diverse resource mix suggests that Igiugig could achieve very high levels (70% or more) of annual renewable generation contributions. A critical step in pursuing this path is identifying the mix of energy assets (generation and storage) that best meets the community's budget, needs, and goals. The assets that a community installs early in their grid-modernization initiative can constrain the options that are economical at later stages, which may lead to sub-optimal solutions. This is where technical and economic analysis of potential scenarios (i.e., distinct mixes of energy assets) can be useful in identifying the most promising pathways so that a community can make informed and strategic decisions about the assets they install. These analyses are most accurate and informative when they are based on actual technology performance and cost data. As the RivGen project continues to operate and generate this data, we will be better prepared to evaluate the technology's long-term viability and to identify research areas that would improve it. Igiugig's energy projects are at the cutting edge of two intersecting technology areas: 1) deploying an operational river hydrokinetic turbine, and 2) integrating renewable energy sources to achieve very high percent renewables. If these projects are successful, the lessons learned and technologies developed could be valuable for other microgrids around the world. Igiugig's unique resource mix make it an ideal location for this work, and the community's organizational strength make it an ideal partner in this ground-breaking work. Ongoing support for technical assistance to manage and address technical challenges along the way will maximize the probability of project success.

13 HYDRO ENERGY↗
NASA NTRS1985

Some observations on the occurrence of striation heating

Various wind tunnel flow visualization techniques have revealed the presence of striations on the surface of both simple geometries and complex winged entry configurations over a wide range of test conditions. The striations are attributed to streamwise vortices embedded in the boundary layer which produce locally enhanced heating levels. Mechanisms for such vortex formation are suggested based on observation of their occurrence on the simple configurations. These mechanisms are then related to striations observed in the wind tunnel on windward surfaces, swept wing leading edges and on the side fuselage of winged entry bodies. Flight data obtained on the side fuselage of ASSET and Shuttle support the conclusions derived from wind tunnel results. Quantitative criteria for the appearance of striations resulting from some of these mechanisms are presented. It is shown that the presence of embedded vorticity may be a consideration in the design of thermal protection systems for advanced winged entry vehicles.

Kipp, H. W.↗
DOE OSTI2018

Enhancing Clean Energy Innovation Ecosystem Discovery Tool

During March 2016, the DOE’s Office of Energy Policy and Systems Analysis (EPSA) sought a methodology to identify and quantify the strength of the existing clean energy innovation ecosystems (IE) in the U.S. and their characteristics. Oak Ridge National Lab (ORNL) did a pilot study (Phase 1) and demonstrated the feasibility of an application comprised of natural language processing, link analysis, and other computational techniques to transform text and numerical data into metrics on clean energy innovation activity and geography. The data-collection, ingest and analytics pipelines were combined with an advanced user interface, together known as the Ecosystem Discovery Tool, to enhance DOE’s understanding of existing geographic innovation clusters. During Phase 2 of this project, this tool has been further enhanced by integrating new data sets and through backend software architecture changes, validation and bug fixing, making it a much more robust and powerful application. The tool’s user interface is a lot more intuitive, which enables a user to visualize the IE rankings for various geographic regions(CBSA, state level) for different clean energy technologies and seek automated insights. ORNL also created a DOE-specific dashboard that allows the user to visualize and analyze federal funding from various offices including Energy Efficiency and Renewable Energy(EERE), Office of Electricity(OE), Fossil Energy(FE), and Nuclear Energy(NE). During Phase 1 of this project, EPSA defined a clean energy innovation ecosystem as the overlap of five Ecosystem Components: 1) nascent clean energy Indicators, 2) investors, 3) enabling environment, 4) networking assets and 5) large companies. EPSA and ORNL worked together to collect data for each component: 1) small and medium companies, ARPA-E awardees, SBIR awardees, patents, publications, ERCs for Nascent Clean Energy Indicators; 2) qualified investors; 3) the Clean Edge Policy Index/DSIRE for the Enabling Environment; 4) universities, national laboratories, ERCs and incubators for Networking Assets; and 5) large companies and a subset of the Russell 1000 list for Large Companies. The ORNL team created a visual tool based on Tableau that integrated ecosystem component data to score, rank and map IEs. The tool was created with the flexibility to allow the user to choose the weights of each of the five ecosystem components and the subcomponents. This flexibility allows the user to visualize different subsets and to use the underlying data for different types of analysis. During Phase 2 of this project, the backend database and computation process have undergone major changes to provide a much more refined user-interface and added new features into the scoring algorithm. This phase also involved addition of newer databases such as a list of Energy Research Centers (ERC) ,DSIRE, and funding data from EERE, FE, NE, and OE to provide more granular information and more accurate/better quantification.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Hydropower Infrastructure - LAkes, Reservoirs, and RIvers (HILARRI), v4

HILARRI is a database of links between major datasets of operational hydropower dams and powerplants, and inland water bodies. These connections are critical for conducting large-scale analysis of hydropower infrastructure and their associated natural and engineered water systems. Features include: – Dams from the National Inventory of Dams (2025) and the Global Reservoir and Dam Database (GRanD v1.3) – Hydropower plants from the Existing Hydropower Assets dataset (EHA 2025) – Power plants that are listed in the 2025 U.S. Hydropower Development Pipeline Data or were listed in previous versions of the dataset These hydropower infrastructure features are linked to several major datasets that provide hydrologic and hydraulic information relevant for analysis of hydropower systems that includes the integral water resources. That information comes from: – Products from the National Hydrography Dataset (NHD) – NHDPlusV2 Medium Resolution river network flowlines, – NHD waterbodies (limited to lakes and reservoirs), – NHD Watershed Boundary Dataset (HUC12-level for the Conterminous United States (CONUS)) – NHD High Resolution waterbodies – HydroLAKES water bodies (lakes and reservoirs) – LAGOS-US lakes and reservoirs – EPA National Lakes Assessment (2007, 2012, 2017, and 2022) – The Reservoir Sedimentation Database (RESSED) – EPA SuRGE sampling locations Unique identifiers are used to facilitate joining to the original full datasets. For example, characteristics of NHD flowlines such as estimated average flow rate can be joined from the NHDPlusV2 dataset to a dam or power plant listed in HILARRI based on the ID field, “COMID”, that is common to both datasets. HILARRI only includes basic information about identifiers, location, and data quality or usage notes. It does not contain the attributes or time series data associated with these sites. The HILARRI dataset incorporates information from several datasets to facilitate more effective and accurate analysis of hydropower infrastructure and their associated waterbodies. For example, dams were checked against the most recent American Rivers Dam Removal Database to identify and flag facilities that may no longer exist. Additionally, dams that are listed multiple times in the NID are identified and flagged to avoid double-counting when analyzing and summarizing information. Other quality flags include certainty of operational hydropower (i.e., if one or more datasets indicates hydropower at a particular location), whether an associated water body is accurate or composed of multiple polygons, or whether there is a known issue with reported characteristics in one of the underlying datasets. These additional data flags are designed to increase confidence in data usage for individual to large-scale analyses.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗
DOE OSTI2015

Total Dissolved Gas Prediction and Optimization in RIVERWARE

Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results indicate excellent model performance with coefficient of determination values exceeding 92% for all sites. This approach enables model extension to an increasingly wider array of hydropower plants, i.e., with the proper data input, TDG uptake can be calculated independent of actual physical component design. The TDG model is used as a module in the systematic optimization framework of RiverWare, a river and reservoir modeling tool used by federal agencies, public utility districts, and other dam owners and operators to forecast, schedule, and manage hydropower assets. The integration and testing of the TDG module within RiverWare, led by University of Colorado's Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), will allow users to generate optimum system schedules based on the minimization of TDG. Optimization analysis and added value will be quantified as system wide reductions in TDG achieved while meeting existing hydropower constraints. Future work includes the development of a method to predict downstream reservoir forebay TDG levels as a function of upstream reservoir tailrace TDG values based on river hydrodynamics, hydro operations, and reservoir characteristics. Once implemented, a holistic model that predicts both TDG uptake and transport will give hydropower operators valuable insight into how system-wide environmental effects can be mitigated while simultaneously balancing stakeholder interests.

13 HYDRO ENERGY↗
DOE OSTI2024

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data. Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

Improvements in CALIOP Smoke Optical Depth over Clouds

Smoke over marine stratocumulus is ubiquitous off the south west coast of Africa during biomass burning season. The vertical profile measurements provided by the CALIOP lidar are successfully able to distinguish between smoke and underlying clouds. With over 14 years of observations, the CALIOP data set is a valuable asset for quantifying the radiative impact of smoke over clouds in this region. However past studies have shown that CALIOP overestimates the base altitudes of strongly attenuating smoke layers. This is because CALIOP layer detection operates on the 532 nm attenuated backscatter signal. Smoke strongly attenuates light at this wavelength, so CALIOP feature detection at times assigns a base altitude that is higher than the true layer base for optically thick layers. This can be confirmed by the 1064 nm attenuated backscatter signal, also measured by CALIOP. In order to improve the AOD for smoke over clouds, a new algorithm has been implemented in for an upcoming CALIOP level 2 data release that will extend the base altitudes of smoke layers over clouds. Tunable restrictions are put in place to ensure that smoke bases are only extended within a reasonable smoke-to-cloud gap distance and only when there is strong reason to believe that smoke exists within the gap. This presentation will summarize the new smoke base extension algorithm and summarize its performance. We will demonstrate that base extension is primarily invoked off the south west coast of Africa as expected. We will also quantify the increase in smoke AOD that will be reported in the upcoming level 2 data release.

Jason L Tackett↗
DOE OSTI2017

PV Systems Reliability and Outreach

The project purpose was to collaborate with the Electric Power Research Institute (EPRI) to reach out to the photovoltaic (PV) industry to cooperate, collaborate and facilitate establishment and access to PV plant data for use in the Photovoltaic Reliability Operations and Maintenance (PVROM) database. Sandia National Laboratories (SNL) and EPRI conducted this outreach to expand and accelerate the implementation of PVROM by gathering more data for analyzing trends, with a goal of accelerating the adoption of PV systems as a primary power generation source in the United States. SNL and EPRI analyzed the data from the PVROM database to assess industry trends in operations and maintenance (O&M) and develop guidelines for the industry. More specifically, this project was intended to leverage SNL’s expertise in PV plant reliability data collection and analysis, with data sharing partners that own or operate PV systems who wanted to learn about rigorous reliabilitybased data collection to track issues over time and improve O&M activities. The partnership also worked to host multiple workshops as part of the SNL/EPRI PV Systems Symposium to gather industry feedback on O&M process improvement and data standards, and share insights learned from the collaboration between SNL and EPRI in the area of PV system reliability. Additional outreach included multiple ‘expert elicitation’ interviews led by EPRI to gather best practices and paths forward for improving/standardizing PV plant O&M and asset management practices. Technical accomplishments included further development of the PVROM database process, sharing best practices for reliability data collection and improving industry understanding of existing O&M practices, important knowledge, and new and novel techniques for benefitting EPRI utility partners and the broader PV industry. Improved reliability at a PV power plant leads to a lower levelized cost of energy (LCOE), which is reflected most directly in its operating expenses. Electric utilities that utilize PV as a larger share of plants they own and operate are interested in having a high degree of availability or ‘uptime’, similar to other power generation sources in their service area. Having low cost, reliable PV generation can lead to fewer costs that need to be recovered by the utility over the lifetime of the power plant, and less regulatory uncertainty when considering bulk transmission and distribution system reliability. The public and taxpayers benefit by the electric utility passing through lower electricity costs.

14 SOLAR ENERGY↗
DOE OSTI2024

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY↗