Search NASA⌕ Search

SEARCH · Search NASA

Results for “Capacity Factor”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Impacts of Distinct Flexibility Enhancements on the Value and Dynamics of Natural Gas Power Plant Operations

The rapid increase of renewable generation and its anticipated continued growth requires greater operational flexibility in modern power systems. Previous studies explored the addition of more flexible resources to improve system flexibility, but this may also be achieved at lower cost by enhancing existing power plants via flexibility retrofits. Potential flexibility upgrades to existing thermal plants include modifications that enable faster ramp rates, increase maximum load levels, decrease minimum load levels, and provide faster and lower cost startup operations. In this paper, we focus on improvements to existing natural gas combined cycle generators, and apply a unit commitment model to analyze the impact that each specific upgrade has on their operational dynamics and profitability from both the system perspective and from the asset owner perspective. We show that the value of each type of flexibility improvement varies depending on the capacity factor and usage pattern of the generator before the upgrade, and that the relative benefit of each type of flexibility varies. We demonstrate diminishing returns to increased flexibility when upgrading multiple generators simultaneously. Sensitivity tests for several shares of renewable generation, different generation mixes and different net load realizations confirm the generality of the results shown.

03 NATURAL GAS↗
DOE OSTI2018

Production of Synthetic Natural Gas From Carbon Dioxide and Renewably Generated Hydrogen: A Techno-Economic Analysis of a Power-to-Gas Strategy

Power-to-gas to energy systems are of increasing interest for low carbon fuels production and as a low-cost grid-balancing solution for renewables penetration. However, such gas generation systems are typically focused on hydrogen production, which has compatibility issues with the existing natural gas pipeline infrastructures. This study presents a power-to-synthetic natural gas (SNG) plant design and a techno-economic analysis of its performance for producing SNG by reacting renewably generated hydrogen from low-temperature electrolysis with captured carbon dioxide. The study presents a 'bulk' methanation process that is unique due to the high concentration of carbon oxides and hydrogen. Carbon dioxide, as the only carbon feedstock, has much different reaction characteristics than carbon monoxide. Thermodynamic and kinetic considerations of the methanation reaction are explored to design a system of multistaged reactors for the conversion of hydrogen and carbon dioxide to SNG. Heat recuperation from the methanation reaction is accomplished using organic Rankine cycle (ORC) units to generate electricity. The product SNG has a Wobbe index of 47.5?MJ/m3 and the overall plant efficiency (H2/CO2 to SNG) is shown to be 78.1% LHV (83.2% HHV). The nominal production cost for SNG is estimated at 132 $/MWh (38.8 $/MMBTU) with 3 $/kg hydrogen and a 65% capacity factor. At U.S. DOE target hydrogen production costs (2.2 $/kg), SNG cost is estimated to be as low as 97.6 $/MWh (28.6 $/MMBtu or 1.46 $/kgSNG).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling

Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.

Meteorology & Atmospheric Sciences↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability

Abstract Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes. Significance Statement Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.

Coburn, Jacob↗
DOE OSTI2025

Renewable Energy Potential Model: Hawaii Geothermal Supply Curves

This dataset extends the development of the Renewable Energy Potential (reV) model to include geothermal energy, with a specific focus on Hawaii. Provided here are the results of two scenarios that were modeled for geothermal energy in Hawaii: binary enhanced geothermal systems (EGS) at a depth of 2.5 km and hydrothermal binary systems at a depth of 1.5 km. The resource data for both scenarios were derived from Lautze and Haskins (2024) using an exponential method. The PFA probability of heat map was used as a look up table for which temperature gradient to use (Lautze and Haskins, 2024). The dataset provides geospatial and techno-economic details for evaluating geothermal energy potential. It includes spatial coordinates, estimated capacity factors, developable area, resource potential, and annual energy production metrics. Economic details such as levelized cost of electricity (LCOE), site development costs, transmission costs, and fixed-charge rates are also included. The reV model, originally developed for wind and solar energy, incorporates these variables to evaluate deployment constraints related to land use, environmental and cultural factors, and grid integration.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Feasibility Study of Large-Scale Energy Storage in the Earth

Energy storage systems on a large scale are needed when there is a mismatch between electricity generation and demand rates. The mismatch may be due to a variety of reasons: 1. Generation rates of solar are cyclic and are often out of phase with the demand cycles. 2. Generation rates of wind are unpredictable. Furthermore, high-efficiency, low-carbon power plants (e.g., nuclear) typically have high capital cost and low operating cost. Such plants are designed for continuous base-load operation and require a high capacity factor for economic viability (Forsberg, 2017). For these reasons, it is advantageous to be able to store energy when not needed and use it when needed. Our proposed process, called the Air Earth Battery, has been developed to accomplish the task of energy storage and dispatch, using a combination of compressors, expanders, heat exchangers, and subsurface porous, permeable rock formations. This technology utilizes two issued U.S. Patents (Buscheck, 2017a; 2017b), one filed U.S. Patent Application (Buscheck, 2017c), and one filed U.S. Provisional Patent Application (Buscheck and Upadhye, 2018).

25 ENERGY STORAGE↗
DOE OSTI2019

California Time-of-Use (TOU) Transition: Effects on Distributed Wind and Solar Economic Potential

Time-of-use (TOU) retail energy rates price electricity differently by the time of day, thereby communicating to consumers the costs of supplying electricity throughout the day. This study evaluates the impact of Decision D.15.07-001, which mandates a transition to default TOU rates in California, on the economic viability of behind-the-meter distributed wind and solar systems. We assess viability through 'economic potential,' a metric we define as the amount of generation capacity that exceeds a specified rate of return (5.4%) and therefore would be economic to construct; we do not attempt to project deployment or adoption. In addition, we identify cost improvements needed for a robust distributed wind market and the specific counties and sectors with substantial economic potential. Over the scenarios considered, model results indicate realistic pathways to reaching a robust, 1-GW distributed wind market in California though solar economic potential was found to be substantially larger than that of wind. Distributed wind's capacity factor does not appear to be strongly correlated to the periods of peak electricity prices as set by utility's TOU periods. Because of this disassociation and nuances in the billing of tiered electricity, the transition to TOU is projected to moderately decrease distributed wind economic potential and increase that of distributed solar. However, a limitation of this analysis is that it does not factor in the change in rate values as California works toward its goal of 100% renewables. As variable renewable energy penetration increases to meet this goal, our results suggest that wind generation will become increasingly correlated to periods of peak electricity prices. Increased variable renewable penetration, especially of solar, is likely to shift periods of higher electricity demand to later in the evening, and any periodic adjustments in TOU periods to reflect these new periods of demand will positively affect the value of wind generation more than the value of solar generation. High distributed wind capital costs are a significant barrier to large scale adoption; we explore the sensitivity of capital cost reductions on distributed wind economic potential. We find that distributed wind economic potential increases substantially in 2020 for capital costs below 3 dollars/W - particularly for residential- and commercial-scale turbines; capital costs must fall below 2 dollars/W in 2030 to support a significant increase in economic potential, in large part due to the expected continued cost reductions in solar. We identified an upper limit to the state's behind-the-meter distributed wind economic potential at approximately 5 GW. Overall, California exhibits over 1 GW of economic potential for distributed wind by 2030, even with the moderate decrease in potential under TOU. This potential is represented mostly by Southern California, which sees the most notable increase in economic viability as capital expenditure prices decline.

17 WIND ENERGY↗
DOE OSTI2019

Initial Thermal Energy Yield Potential for the Use of Concentrating Solar Power (CSP) for Coal Hybridization in India

The hybridization of concentrating solar power (CSP) with coal-based power generation in India may serve to mitigate fossil fuel use externalities. Assuming parabolic trough systems without storage, this report estimates the upper bound on thermal energy production from India's solar resource to be 633,000 terawatt-thermal (TW th ) annually. Moreover, considering land characteristic constraints, contiguous solar fields (SF) area limitations, and existing coal plant proximity, we produce technical potential estimates. Within 1,000 meters (m) of suitable coal plants, we find the average capacity factor to be 21.1% and the potential for 102,555 gigawatt-hours thermal (GWh th ) aggregated from 25 megawatt thermal (MW th ) CSP SFs. Only about 10% of the land within 1,000 m of each existing coal plant is anticipated to be suitable for hybridization development, and on average this land is expected to support a 43 MW th SF that yields 81 GWh th annually. Chhattisgarh and Tamil Nadu are particularly suited to CSP-coal hybridization and the abundance of suitable land in these states would allow SFs to provide 129 GWh th annually to each coal plant on average. Future research will assess the financial viability of hybridization and explore coal plant optimization strategies that integrate CSP-derived heat (e.g. feedwater heating or potentially coal drying).This study shows significant CSP-coal hybridisation potential for the existing coal plants in India. This preliminary study suggests CSP-coal hybridization may play a supporting role in India's energy system, but it's future is still largely uncertain. This is an area of considerable interest in India, and the methodology could also be adapted for other areas of the world like the United States.

14 SOLAR ENERGY↗
DOE OSTI2019

Utility-Scale Solar: Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States (2019 Ed.)

The utility-scale solar sector has led the overall U.S. solar market in terms of installed capacity since 2012. In 2018, the utility-scale sector accounted for nearly 60% of all new solar capacity, and is expected to maintain its market-leading position for at least another six years. More than three-quarters of all states, representing all regions of the country, are now home to one or more utility-scale solar projects. This report—the seventh in an ongoing annual series—provides in-depth data-driven analysis of the utility-scale solar project fleet in the United States. Drawing on empirical project-level data from a wide range of sources, this report analyzes technology trends, installed project prices, operating costs, capacity factors, power purchase agreement (“PPA”) prices, the levelized cost of solar energy (LCOE), and the market value of solar. The report also includes data and observations about completed or recently announced solar+storage projects. Given its current preeminence in the market, utility-scale PV also dominates much of this report, though data from CPV and CSP projects are also presented where appropriate.

14 SOLAR ENERGY↗
DOE OSTI2020

Scoping Analysis of Sodium Cooled Fast Spectrum Test Reactor Cores

A team from the national laboratories conducted a study that assessed advanced reactor technology options and the irradiation needs of a broad group of stakeholders. This identified a gap in the fast neutron irradiation capability - the need for a test reactor that can deliver high neutron fluxes of fast neutrons. The study compared fast and thermal neutron irradiation technology options based on technology maturity and the ability to meet strategic objectives, along with pathways to deployment and tradeoffs in mission. It also provided a recommendation on specific technology options to address the current gap in fast neutron irradiation capabilities. In this context, a detailed scope of work was prepared that pertains to a trade study focusing on the core of a fast neutron spectrum test reactor. This report presents the main results obtained by a team of Argonne National Laboratory (ANL) and Idaho National Laboratory (INL) scientists. It aims at developing an overall understanding of how the various areas important to the design and successful operation of such a facility interact with one another. Developing a sense of the relevant sensitivities at a systems level creates an understanding of where and how margins may be available to improve performances (e.g., flux level, capacity factor, and thermal hydraulic limits). Emphasis is given to the reactor (core design options and safety) and its fuel cycle (fuel supply and fabrication, as well as spent fuel management).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Evaluation of Steam Cycle Upgrades to Improve the Competitiveness of U.S. Coal Power Plants (Final Scientific / Technical Report)

Increasing the competitiveness of the existing pulverized-coal utility fleet in the United States may be achieved by decreasing heat rate, via increases in steam cycle efficiency through upgraded steam temperatures and use of latest technology available in steam turbine and blading design. The average net plant efficiency of the US coal-fired fleet is approximately 33% (HHV). Plant efficiency increases to approximately 41.4% (HHV) at 1,350°F (732°C) steam temperature. However, achieving these Advanced Ultra-Super Critical (AUSC) steam conditions requires the use of advanced high-temperature materials. While there has been a significant amount of DOE-funded materials R&D, most of the related design work has focused on new (greenfield) units, rather than on opportunities to retrofit this advanced technology to the existing utility fleet. If technology, based upon the advanced materials required for AUSC steam conditions, may be applied to the existing fleet, using an economically viable retrofit, a higher capacity factor can be expected as a result of the increased plant competitiveness. The Electric Power Research Institute (EPRI) was awarded a project by the US Department of Energy to examine the technical and economic feasibility of a series of steam cycle upgrades to the two most prevalent types of U.S. coal power plants: 2,400 psig (16.6 MPa) subcritical and 3,500 psig (24.1 MPa) supercritical pulverized coal units. The nine upgrade options that were originally being considered included increasing the main and reheat steam temperatures from 1,000°F (538°C) to 1,100°, 1,200°, and 1,350°F (593°C, 649°C, and 732°C) while holding the steam pressures constant at their original design values, and cases where just the main steam or reheat steam temperatures were increased. The objective was to minimize the modifications required to the existing power plant while still providing a significant improvement in heat rate. The upgrade options assumed that the boiler enclosure envelope remained unchanged from each base case, and that all applicable OEM design guidelines for normal commercial units were imposed. For the highest temperature supercritical case, an option of using a low-pressure molten salt loop to transfer heat from the furnace to the steam was examined. The first major task of the work scope was designed to examine the technical feasibility of various upgrade options, while the subsequent work determined economic viability of the technically feasible upgrade options. Prior to evaluating the effect of these increased temperatures, a “base case” model of a subcritical and supercritical PC boiler was created, which was used for comparative purposes. Upgrade options were evaluated at full-load, part-load and dynamic transient conditions. Once the technical feasibility of each upgrade option was evaluated, the economic value of the heat rate improvement of each feasible option was determined by detailed modeling of unit dispatch in several regional power markets. The dispatch model was used to estimate the amount of revenue from power sales the upgraded unit would receive in comparison to a non-upgraded version of the same power plant. As a parallel task to the dispatch analysis, the capital cost of implementing the upgrades was estimated. The capital cost estimates were then compared to the increased revenue estimated by the dispatch modeling to determine the economic attractiveness of each upgrade option. Several upgrade options were determined to be technically feasible. The net present value (NPV) of the costs for steam cycle upgrades considered in this study ranged from approximately $\$$111 to $\$$130 million. The economic modeling results show that the unit dispatch changes resulting from steam cycle upgrades are relatively small, due largely to heat rate (and operating cost) changes being relatively small. Additionally, the cost of each upgrade exceeds the net revenue increases associated with the upgrade case. Note that the breakeven values are higher for subcritical retrofits, but the capital costs for the subcritical upgrades are also slightly higher. In typical new pulverized coal plants, fuel accounts for approximately 25% of the cost of electricity (COE), while capital costs represent around 50% of the COE. Therefore, in order to improve the heat rate by 4% one can only afford to increase the capital cost by 2%, at the same cost of electricity. The conclusion of this study is that without a cost for emitting CO 2 , it will be difficult to pay for significant efficiency improvements on plants firing low cost coals.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Benchmarking Utility-Scale PV Operational Expenses and Project Lifetimes: Results from a Survey of U.S. Solar Industry Professionals

This paper draws on a survey of solar industry professionals and other sources to clarify trends in the expected useful life and operational expenditure (OpEx) of utility-scale photovoltaic (PV) plants in the United States. Solar project developers, sponsors, long-term owners, and consultants have increased project-life assumptions over time, from an average of ~21.5 years in 2007 to ~32.5 years in 2019. Current assumptions range from 25 years to more than 35 years depending on the organization; 17 out of 19 organizations surveyed or reviewed use 30 years or more. Levelized, lifetime OpEx estimates have declined from an average of ~$\$$35/kW DC -yr for projects built in 2007 to an average of ~$\$$17/kW DC -yr in 2019. Across 13 sources, the range in average lifetime OpEx for projects built in 2019 is broad, from $\$$13 to $\$$25/kW DC -yr. Operations and maintenance (O&M) costs—one component of OpEx—have declined precipitously in recent years, to $\$$5-8/kW DC -yr in many cases. Property taxes and land lease costs are highly variable across sites, but on average are—together—of similar magnitude. Other OpEx line items include security, insurance, and asset management. Given 2007-2009 values for not only project life and OpEx but also other drivers of the levelized cost of energy (LCOE, excluding the investment tax credit), the LCOE for utility-scale PV projects built from 2007 through 2009 averaged $\$$305 /MWh. Using 2019 values for all parameters yields an average LCOE of $\$$51 /MWh. The decline in LCOE from $\$$305 /MWh to $\$$51 /MWh was predominantly caused by reductions in up-front expenditures (and, to a much lesser extent, by changes in capacity factors, financing costs, and tax rates), but 9% ($\$$22 /MWh) of the overall decline is due to improvements in project life and OpEx. Project life extensions and OpEx reductions have had similarly sized impacts on LCOE over this period, at $\$$11 /MWh each. Had project life and OpEx not improved over the last decade, LCOE in 2019 would have instead been $\$$73 /MWh—43% higher. Given the limited quantity and comparability of previously available data on these cost drivers, the data and trends presented here may inform assumptions used by electric system planners, modelers, and analysts. The results may also provide useful benchmarks to the solar industry, helping developers and assets owners compare their expectations for project life and OpEx with those of their peers.

14 SOLAR ENERGY↗
DOE OSTI2020

Modeling the Impact of Flexible CHP on the Future Electric Grid In California

Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States. Typically fueled with natural gas, a CHP system combines a prime mover (such as a reciprocating engine) with a generator and heat recovery equipment, allowing operation at very high efficiencies (65–85%). Traditionally, CHP systems have been configured to serve local electrical and thermal loads at the sites where they are deployed. Units are sized to ensure a high capacity factor for the equipment, and the electricity generated tends to be used on site. CHP units in the United States already generate over 12% of the nation’s electricity. However, CHP’s potential benefits could be much greater if power generated could be used beyond the site, because the analysis was performed under the assumption that sites could use all the thermal output. Analysis of a few key sectors confirmed that this assumption is valid (for more information, see Appendix E). Those benefits could include improved grid reliability and resilience, as well as lower-cost options for providing energy and other grid services. The potential benefits also align well with grid modernization objectives, as shown in Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States., and greater electrification of loads, driven by carbon reduction priorities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Technology-Enabled Risk-Informed Maintenance Strategy to Minimize Operation and Maintenance Costs

The domestic fleet of nuclear power plants (NPPs) is facing a unique economic sustainability challenge in today’s energy market due to high total operating costs. One of the major contributors to the total operating cost of an NPP is the operations and maintenance (O&M) budget, which includes labor-intense preventive maintenance (PM) programs. PM programs involve manually performing inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, as well as time-based replacement of assets, irrespective of individual asset condition. This approach, combined with the push to achieve high capacity factors, has resulted in a labor-centric business model. It is time to transition from this labor-centric business model to a technology-centric business model that will enable an optimal maintenance strategy by eliminating unnecessary costs associated with time-based PM activities. To enable this transition, the commercial nuclear industries are utilizing and developing reliable methodologies, based on available state of the art technologies, which facilitate assessing equipment condition and the dynamic risk of failure. The U.S. Department of Energy’s Idaho National Laboratory (INL) under the Light Water Reactor Sustainability (LWRS) Program is partnering with PKMJ Technical Services and Public Service Enterprise Group (PSEG) Nuclear, LLC to develop and demonstrate a deployable risk-informed predictive maintenance strategy to eliminate unnecessary O&M costs for an identified plant system, laying the foundation for scale-up to the entire plant. Recently developed technologies such as advanced wireless and wired sensors, data analytics, and risk assessment methodologies will support this transition. The technology-centric O&M model will result in significant automation and lay the foundation for real-time condition assessment of plant assets, thus enabling condition-based maintenance and enhancing plant safety, reliability, and economics of operation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗
DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Integrated Design of a Robust System for Inertial Fusion Energy

For inertial fusion energy (IFE) to be successful, designs need to work robustly including both target physics and engineering considerations. For a power plant to be reliable and have a high operating capacity factor, the integrated design of the target, driver, target fabrication, target injection system, and chamber all need to work together in way that is robust and repeatable to expected variations. One of the lesson’s learned from our experience at NIF is that designs that are sensitive have not performed as expected – even in single shot mode. The lesson’s learned from NIF should be folded into creating integrated designs for IFE and for evaluating the tradeoffs between the different parts of the IFE system. To do so, we propose using the NIF 1.3 MJ yield shot/design (N210808) as a starting point of a study of the feasibility of indirect drive designs for IFE. If the hohlraum inefficiency precludes indirect drive, the study would include direct drive or fast ignition versions of this design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗