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At least 235 records · Page 13

What Makes You Hold on to That Old Car? Joint Insights From Machine Learning and Multinomial Logit on Vehicle-Level Transaction Decisions

What makes you hold on to that old car? While the vast majority of household vehicles are still powered by conventional internal combustion engines, the progress of adopting emerging vehicle technologies will critically depend on how soon the existing vehicles are transacted out of the household fleet. Leveraging a nationally representative longitudinal data set, the Panel Study of Income Dynamics, this study examines how household decisions to dispose of or replace a given vehicle are: 1) influenced by the vehicle’s attributes, 2) mediated by households’ concurrent socio-demographic and economic attributes, and 3) triggered by key life cycle events. Coupled with a newly developed machine learning interpretation tool, TreeExplainer, we demonstrate an innovative use of machine learning models to augment traditional logit modeling to both generate behavioral insights and improve model performance. We find the two gradient-boosting-based methods, CatBoost and LightGBM, are the best performing machine learning models for this problem. The multinomial logistic model can achieve similar performance levels after its model specification is informed by TreeExplainer. Both machine learning and multinomial logit models suggest that while older vehicles are more likely to be disposed of or replaced than newer ones, such probability decreases as the vehicles serve the family longer. Pickup trucks and sport utility vehicles are less likely to be disposed of or replaced than cars, and leased vehicles are more likely to be transacted than owned vehicles. We find that married families, families with higher education levels, homeowners, and older families tend to keep their vehicles longer. Life events such as childbirth, residential relocation, and change of household composition and income are found to increase vehicle disposal and/or replacement. We provide additional insights on the timing of vehicle replacement or disposal, in particular, the presence of children and childbirth events are more strongly associated with vehicle replacement among younger parents.

33 ADVANCED PROPULSION SYSTEMS↗

Expected occurrence of wildlife in US Atlantic offshore wind areas

Offshore wind energy has entered a pivotal phase of development for the U.S. Atlantic Outer Continental Shelf (OCS), a region that supports critical habitats, migratory corridors and flyways for many marine species. Assessing where and when marine wildlife occurs is a crucial first step in developing a risk assessment framework to evaluate potential risks and impacts of offshore wind development. In this study, we perform this initial assessment by evaluating the expected occurrence of marine mammal, seabird and sea turtle taxa in areas of interest to identify patterns and potential areas of concern. Specifically, this work depicts the expected monthly density of 84 marine species and taxa within each of the 29 active wind energy lease areas plus a 10 km buffer to account for nearby activity. We then compare these densities to subregional thresholds, evaluated as the 90th percentile of the subregion’s monthly density, to provide comparisons across the shelf region. This analysis synthesizes the most recent spatial distribution models of 31 marine mammal taxa (26 species and 5 guilds), 49 seabird species and 4 sea turtle species to provide a unified evaluation of the major marine wildlife in the region. Out of the 84 species and taxa analyzed, 56 exhibit levels of expected density in wind energy areas that exceed the corresponding 90th percentile subregional threshold at some point throughout the year. These results represent an initial assessment in the broader Occurrence, Exposure, Response, and Consequence (OERC) framework, originally developed by the U.S. Navy for marine species risk assessments. These results offer valuable guidance to marine spatial planners, management agencies and offshore wind developers on the expected locations and timing of interaction risk to wildlife species in or near wind energy areas across the region.

17 WIND ENERGY↗

Energy Efficiency Package for Tenant Fit-Out: Laboratory Testing and Validation of Energy Savings and Indoor Environmental Quality

Approximately 40% of the total U.S. office floor space of 1.5 billion sq.m (16 billion sq.ft.) is leased space occupied by tenants. Tenant fit-out presents a key opportunity to incorporate energy efficiency within the real estate business cycle. We designed a package of energy efficiency measures tailored to the scope of a tenant fit-out. This tenant fit-out package (TFP) includes advanced lighting and heating, ventilating and air-conditioning (HVAC) controls as core measures, with ceiling fans, automated shading, and plug load controls as additional optional measures. We conducted laboratory testing of six configurations of the package to evaluate energy savings, indoor environmental quality, and identify installation, commissioning, and operational issues. Combined savings for HVAC, lighting, and plug loads ranged from 33–40%. Lighting savings ranged from 69–83%, and HVAC savings from 20–40%. The laboratory testing also revealed some minor but tractable challenges with installation and commissioning of HVAC controls. Overall, the results demonstrate that significant savings can be realized in existing office buildings by incorporating relatively low-risk, proven measures at the time of a tenant fit-out.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California

Floating offshore wind is being considered in northern California as indicated by the Bureau of Ocean Energy Management’s issuance of a lease consideration in the Humboldt Call Area. Humboldt County offers access to this enormous resource, but local electric load and transmission are limited. The potential impacts of offshore wind generators at three different scales were studied using a regional grid model of Humboldt County. Offshore wind generation was calculated using modeled wind speed data and 12-MW turbine specifications and integrated with projected load and historical generation. Offshore wind farms deployed in the Humboldt Call Area achieve annual capacity factors between 45% and 54% after losses and maintenance. Power output is variable between and within seasons, with full power output 30% of the time and no output approximately 20% of the time. Electricity from a 48-MW wind farm provides 22% of regional load with limited exports. A 144-MW wind farm serves 38% of local load, exporting 40% of its electricity with the extant 70-MW transmission capacity. A full build-out of 1836 MW would result in 88% curtailment with existing transmission. Across scenarios, offshore wind variability necessitates reliance on existing power plants to meet local demand in periods of low wind.

17 WIND ENERGY↗

Unlocking Energy Efficiency: Debunking Myths on the Road to Decarbonization

Energy efficiency is widely recognized as the foundational and most critical strategy for decarbonizing the manufacturing sector. Misconceptions surrounding energy efficiency measures often hinder their widespread adoption. This article aims to debunk five common myths and provides data and resources to help implement efficiency projects faster and more effectively to achieve greater decarbonization. First, the article challenges the myth that organizations have exhausted all possible energy efficiency opportunities by achieving voluntary energy intensity goals or energy performance certification. Second, it also addresses the misconceptions that efficiency projects are capital-intensive, require many qualified specialists, and have long investment return periods. By presenting real-world case studies and referencing commonly found efficiency opportunities, the article illustrates that energy-savings opportunities are ubiquitous. Organizations can use various contracting mechanisms as well as financial and technical resources from utility companies and government programs to lessen their burden. The notion that efficiency measures can be implemented solely in proprietorship facilities is dispelled. This article emphasizes the importance of green leases and explains that aligning decarbonization goals between the lessor and lessee can help drive savings for both parties. Finally, using unbundled renewable energy certificates as the sole pathway to decarbonization is strongly discouraged. By debunking these prevalent myths, this article aims to foster a deeper understanding of energy efficiency’s potential as a cornerstone of decarbonization efforts and to embrace it as a critical pathway toward a sustainable future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Characterizing the Payback and Profitability for Automated Heavy Duty Vehicle Platooning

Heavy duty vehicle platooning under highway operating conditions has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits and the economic viability under real-world operating conditions presents several challenges. The objective of this paper (the third as part of a series) is to analytically quantify the payback and profitability of heavy-duty vehicles platooning across the U.S. Interstate highway system. In this paper, a rigorous assessment of several factors that influence the platooning system payback for an end-user as well as the revenue potential for suppliers who may be utilizing an equipment lease model dependent on end-user savings, is presented. In this assessment key interactions explored include market adoption rates, platooning velocities, platoon-able daily mileage, platooning likelihood, variations in baseline powertrain fuel economy (diesel or electric), price of fuel (diesel or electricity), platooning fuel economy benefits, price of the added technology, and the impact of natural platooning due to traffic interactions. Further, the paper explores the economic impact of higher levels of vehicle automation for the trailing vehicles in the platoon, where extending the driver Hours of Service (HoS) may provide additional financial benefits. While the approach makes use of a limited fidelity vehicle analytical model for longitudinal dynamics and operations economics, the narrative provides application decision personnel with a mechanism and well-defined set of impact factors to consider as part of their architectural selection process.

33 ADVANCED PROPULSION SYSTEMS↗

Examination of Nutrient Sources and Transport in a Catchment with an Audubon Certified Golf Course

Water bodies in the East Bay Regional Park District (EBRPD), California, United States, provide aesthetic value and critical ecosystem services, but are often adversely affected by the activities and infrastructure of the intensely urban environment that surrounds the parks. EBRPD leases a golf course (Tilden Golf Course (TGC)) in Tilden Regional Park, one of its most popular parks located in the Berkeley Hills, which was certified as an Audubon Cooperative Sanctuary in 2013. Nonetheless, application of nutrients and pesticides (fungicides, plant growth regulators and herbicides) are commonly used to maintain turf systems and may be transported via surface runoff or through subsurface drainage to surface waters, leading to the concern that golf courses are a major contributor to water pollution. We studied the possible contribution of nutrients (NO3-N and PO4-P) and pesticides transported via storm-generated surface runoff and via groundwater from TGC to the primary drainage in the watershed, Wildcat Creek. Lake Anza, a popular open water swimming lake, is located downstream from TGC and experiences occasional nutrient-driven algal blooms that have caused swim beach closures. Measured NO 3 -N and PO 4 -P in the stream, at times, exceeded concentration limits of 1 mg/L (as N) and 0.05 mg/L (as P), respectively, considered protective of aquatic ecosystems by the United States Environmental Protection Agency (1986). We found that phosphorous likely has a dominant natural source, but nitrogen is primarily derived from a golf course fertilizer source and its concentration increases in the stream during runoff events, while other soluble species decrease. Analyses of pesticides in water reveal the presence of Azoxystrobin in stream water at the golf course, but with concentrations well below the regulatory limit. These results indicate that all other pesticides applied on TGC are not likely transported to the stream, suggesting future reactive transport research must treat contaminant species independently based on their specific transport behaviors.

54 ENVIRONMENTAL SCIENCES↗

Food, Fracking, and Freshwater: The Potential for Markets and Cross-Sectoral Investments to Enable Water Conservation

Hydraulic fracturing—the injection of pressurized fluid, often water, to increase recovery of oil or gas—has become increasingly popular in combination with horizontal drilling. Hydraulic fracturing improves production from a well, but requires a significant amount of water to do so and could put pressure on existing water resources, especially in water-stressed areas. To supply water needs, some water rights holders sell or lease their water resources to oil and gas producers in an informal water market. These transactions enable the opportunity for cross-sectoral investments, by which the energy sector either directly or indirectly provides the capital for water efficiency improvements in the agricultural sector as a mechanism to increase water availability for other purposes, including oil and gas production. In this analysis, we employ an original water and cost model to evaluate the water market in Texas and the potential for cross-sectoral collaboration on water efficiency improvements through a case study of the Lower Rio Grande Valley in Texas. We find that, if irrigation efficiency management practices were fully implemented, between 420 and 800 million m3 of water could be spared per year over a ten year period, potentially enabling freshwater use in oil and gas production for up to 26,000 wells, while maintaining agricultural productivity and possibly improving water flows to the ecosystem.

Cook, Margaret↗

Mapping Benthic Habitat Conditions and Seafloor Deposits using Sediment Profile Imaging and a Semiautomated Image Processing System

Objectives/Scope: Sediment profile imaging (SPI) technology characterizes in situ physical, geochemical, and biological seafloor features. SPI was required by Mexico’s Agency for Safety, Energy, and Environment in 2017 for environmental baseline surveys (EBS) of oil lease blocks in the southern Gulf of Mexico. Because of its ability to provide information on benthic community health and the distribution of very thin (down to the centimeter scale) layers of deposited materials, SPI technology is highly effective for mapping drill cuttings or drilling muds released around wellheads during exploration or production and documenting their ecological impacts. SPI technology has not been widely used in the oil and gas industry for EBS or other monitoring activities. A primary objective of this work is to improve the transparency and consistency of the SPI data generation and data management process. Methods, Procedures, Process: The SPI camera works like an inverted periscope and obtains an undisturbed 21x15-cm cross-sectional image of the upper sediment column. The camera is internally powered and can be deployed rapidly from a standard winch in depths to 4,000 m. Many stations can be sampled in a single day by “pogo-sticking” across a survey area. Sediment grain size, penetration depth, surface boundary roughness, natural and anthropogenic depositional layers, depth of the oxidized surface sediment layer, maximum biogenic mixing depth, and infaunal successional stage can be directly measured at sea or immediately following the cruise. Final SPI data sets can be provided within a few weeks of the survey. Results, Observations, Conclusions: Details on the features measured in SPI images and the underlying interpretive paradigms are presented. To standardize the SPI data generation process, Integral Consulting Inc. has developed 1) a semiautomated image analysis platform, and 2) a SPI data-specific database architecture that allows both numerical and non-numerical metrics to be incorporated into a standard database structure. An integrated, software-based SPI analysis platform has been developed that imports image files and metadata and provides a graphical user interface. The software automatically stores the data, which can then be reviewed for quality assurance, plotted, statistically analyzed, and mapped or exported to other platforms (e.g., Esri ArcGIS©) for further evaluation. Image processing algorithms have been developed using a combination of open-source and commercially available software packages (e.g., MATLAB® and OpenCV) to automatically quantify key parameters. Novel/Additive Information: SPI technology’s underutilization in the oil and gas industry may be in part due to a lack of standardization in the measurement of basic features in SPI images. A primary objective of this work is to develop a streamlined, standardized, and transparent process for generating and managing SPI data.

02 PETROLEUM↗

Achieving Diesel Powertrain Ownership Parity in Battery Electric Heavy Duty Commercial Vehicles Using a Rapid Recurrent Recharging Architecture

Battery electric vehicles (BEV) in heavy duty (HD) commercial freight transport face challenging technoeconomic barriers to adoption. Specifically, beyond safety and compliance, fleet and operational logistics require both high up-time and parity with diesel system productivity/Total Cost of Ownership (TCO) to enable strong adoption of electrified powertrains. At present, relatively high energy storage prices coupled with the increased weight of BEV systems limit the practicality of HD commercial freight transport to shorter range applications, where smaller batteries will suffice for the mission energy requirements (single operational shift). This paper presents an approach to extend the feasibility of BEV HD trucking for a broad range of applications. The concept is based on the leveraging rapid and recurrent recharging of a BEV HD truck that may either already make frequent stops due to shipment drop-offs/reloading or be required to make frequent stops along with longer missions for recharging. While the challenges of the latter are well appreciated, the concept proposed explores making minimal impact to overall mission time by targeting high C-rate charging while optimizing the frequency (miles) through which these events must occur. The concept optimizes battery size and chemistry, such that the expected life (years and total energy throughput) is balanced with the depth of discharge between recharging events, thus making complete use of the energy available through the life of the battery system. The solution is constrained to minimize the impact on payload capacity. The paper analyzes critical levers in achieving diesel price parity (based on a simplified vehicle TCO), achieved through different purchase options (including lease versus buy) and operational models (half-life swap out). Finally, the paper identifies the application design domain where these solutions are viable with limited impact on fleet operations.

Sujan, Vivek↗

The 2023 National Offshore Wind data set (NOW-23)

Abstract. This article introduces the 2023 National Offshore Wind data set (NOW-23), which offers the latest wind resource information for offshore regions in the United States. NOW-23 supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published a decade ago and is currently a primary resource for wind resource assessments and grid integration studies in the contiguous United States. By incorporating advancements in the Weather Research and Forecasting (WRF) model, NOW-23 delivers an updated and cutting-edge product to stakeholders. In this article, we present the new data set which underwent regional tuning and performance validation against available observations and has data available from 2000 through, depending on the region, 2019–2022. We also provide a summary of the uncertainty quantification in NOW-23, along with NOW-WAKES, a 1-year post-construction data set that quantifies expected offshore wake effects in the US Mid-Atlantic lease areas. Stakeholders can access the NOW-23 data set at https://doi.org/10.25984/1821404 (Bodini et al., 2020).

17 WIND ENERGY↗

Implementation of a Three-Dimensional Planetary Boundary Layer Parameterization in a Coupled Modeling System and Evaluation of "Gray Zone" Simulations of a Wind-Wave Event Off the US California Coast Using Observations

A three-dimensional (3D) planetary boundary layer (PBL) parameterization was added to the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) model and the first coupled atmosphere/wave "gray zone" simulations were carried out using the 3D PBL parameterization. A case study of a significant wind-wave event from 4-8 November 2020 off the US west coast was examined, with a focus on the impacts of the event within an approximate 280x280 km central California coastal region covering the Bureau of Ocean Energy Management Morro Bay wind energy lease area. Simulations with both one-dimensional (1D; Yonsei University) and 3D PBL parameterizations were examined in this nest with ..delta..x=400 m. Two-way coupling was active, with near-surface winds feeding back to the wave model and bulk wave statistics feeding back to the atmospheric model. Both simulations compared favorably with buoy observations in capturing the timing and magnitude of wind speed, temperature, dewpoint, and significant wave height, as the front associated with the maritime weather system moved southward across coastal California. However, wind speed errors over land were larger. Time series of the vertical profile of winds below z=250 m from the simulations compared favorably with observations from the US Dept. of Energy Morro Bay Doppler lidar buoy. Differences between the coupled 1D and 3D PBL simulations were minor. The most notable difference was that the simulation using the 3D PBL parameterization had approximately 10 % weaker winds at the peak of the event causing 10 % lower significant wave heights. This difference was shown to be mostly due to differences in the vertical mixing treatment between the parameterizations, in particular the nonlocal downward mixing of higher momentum air in the 1D Yonsei University parameterization in convective conditions. Overall, this work demonstrates that the 3D PBL parameterization can be used in a coupled atmosphere/wave modeling framework with similar behaviors as traditional PBL parameterizations that do not provide horizontal turbulent variances and fluxes.

16 TIDAL AND WAVE POWER↗

Simulated meteorological impacts of offshore wind turbines and sensitivity to the amount of added turbulence kinetic energy

Offshore wind energy projects are currently in development off the east coast of the United States and may influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants may change the local meteorology. In the absence of measurements of potential wind plant impacts on meteorology, simulations offer the next-best possible insight into wake effects on boundary layer height, temperature, fluxes, and wind speeds. However, simulation tools that capture these effects offer multiple options for representing the amount of turbine-added turbulence that may impact assessments of micrometeorological effects. To explore this sensitivity, we compare 1 year of simulations from the Weather Research and Forecasting (WRF) model with and without wind plants incorporated, focusing on the lease area south of Massachusetts and Rhode Island. The simulations with wind plants are repeated to include both the maximum and minimum amounts of added turbulence to provide bounds on the potential impacts. We assess changes in wind speeds, 2 m temperature, surface heat flux, turbulence kinetic energy (TKE), and boundary layer height during different stability classifications and ambient wind speeds over the entire year and compare results for the degree of added turbulence in the wind plant simulations. Because the wake behavior may be a function of boundary layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary layer height. We find that hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds in region 3 of the turbine power curve, although impacts lessen as wind speeds increase past 15 m s−1. In contrast, wind speeds near the surface decrease when no turbine-added turbulence is included but can increase for stably stratified conditions when 100 % of possible TKE is included in the simulations. TKE increases at hub height in the simulations with added TKE for all stability classes, suggesting that atmospheric stability does not immediately modify the TKE generated by turbines. Negligible changes in hub-height TKE manifest in the simulations without the added TKE. At the surface, TKE increases in the simulations with maximum added turbulence only for unstable conditions. In the no-added-turbulence simulations, surface TKE decreases slightly in neutral and unstable simulations. Differences in 2 m temperatures and surface heat fluxes are small but vary considerably with atmospheric stability and the amount of added TKE. Boundary layer heights increase within the wind plant when turbine-added turbulence is included and decrease slightly downwind during stable conditions. In contrast, with no added turbulence, the boundary layer height is in general reduced in stable conditions with wind speeds less than 15 m s −1 and slightly increased in neutral conditions. Finally, shallower upwind boundary layer heights tend to correlate with larger wake areas and distances, though other factors likely also play a role in determining the extent of the wind plant wake. These simulation-based results provide a bound for micrometeorological impacts of wind plant wakes: simulations that couple the atmosphere to the ocean may reduce these impacts, and we await observational verification.

17 WIND ENERGY↗

Linking large-scale weather patterns to observed and modeled turbine hub-height winds offshore of the US West Coast

The US West Coast holds great potential for wind power generation, although its potential varies due to the complex coastal climate. Characterizing and modeling turbine hub-height winds under different weather conditions are vital for wind resource assessment and management. This study uses a two-stage machine learning algorithm to identify five large-scale meteorological patterns (LSMPs): post-trough, post-ridge, pre-ridge, pre-trough, and California high. The LSMPs are linked to offshore wind patterns, specifically at lidar buoy locations within lease areas for future wind farm development off Humboldt and Morro Bay. While each LSMP is associated with characteristic large-scale atmospheric conditions and corresponding differences in wind direction, diurnal variation, and jet features at the two lidar sites, substantial variability in wind speeds can still occur within each LSMP. Wind speeds at Humboldt increase during the post-trough, pre-ridge, and California-high LSMPs and decrease during the remaining LSMPs. Morro Bay has smaller responses in mean speeds, showing increased wind speed during the post-trough and California-high LSMPs. Besides the LSMPs, local factors, including the land–sea thermal contrast and topography, also modify mean winds and diurnal variation. The High-Resolution Rapid Refresh model analysis does a good job of capturing the mean and variation at Humboldt but produces large biases at Morro Bay, particularly during the pre-ridge and California-high LSMPs. The findings are anticipated to guide the selection of cases for studying the influence of specific large-scale and local factors on California offshore winds and to contribute to refining numerical weather prediction models, thereby enhancing the efficiency and reliability of offshore wind energy production.

17 WIND ENERGY↗

Extreme wind shear events in US offshore wind energy areas and the role of induced stratification

As the offshore wind industry emerges on the US East Coast, a comprehensive understanding of the wind resource – particularly extreme events – is vital to the industry's success. Such understanding has been hindered by a lack of publicly available wind profile observations in offshore wind energy areas. However, the New York State Energy Research and Development Authority recently funded the deployment of two floating lidars within two current lease areas off the coast of New Jersey. These floating lidars provide publicly available wind speed data from 20 to 200 m height with a 20 m vertical resolution. In this study, we leverage a year of these lidar data to quantify and characterize the frequent occurrence of high-wind-shear and low-level-jet events, both of which will have a considerable impact on turbine operation. In designing a detection algorithm for these events, we find that the typical, non-dimensional power-law-based wind shear exponent is insufficient to identify many of these extreme, high-wind-speed events. Rather, we find that the simple vertical gradient of wind speed better captures the events. Based on this detection method, we find that almost 100 independent events occur throughout the year with mean wind speed at 100 m height and wind speed gradient of 16 m s -1 and 0.05 s -1 , respectively. The events have strong seasonal variability, with the highest number of events in summer and the lowest in winter. A detailed analysis reveals that these events are enabled by an induced stable stratification when warmer air from the south flows over the colder mid-Atlantic waters, leading to a positive air–sea temperature difference.

17 WIND ENERGY↗

Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble

To accurately plan and manage wind power plants, not only does the time-varying wind resource at the site of interest need to be assessed but also the uncertainty connected to this estimate. Numerical weather prediction (NWP) models at the mesoscale represent a valuable way to characterize the wind resource offshore, given the challenges connected with measuring hub-height wind speed. The boundary condition and parametric uncertainty associated with modeled wind speed is often estimated by running a model ensemble. However, creating an NWP ensemble of long-term wind resource data over a large region represents a computational challenge. Here, we propose two approaches to temporally extrapolate wind speed boundary condition and parametric uncertainty using a more convenient setup in which a mesoscale ensemble is run over a short-term period (1 year), and only a single model covers the desired long-term period (20 year). We quantify hub-height wind speed boundary condition and parametric uncertainty from the short-term model ensemble as its normalized across-ensemble standard deviation. Then, we develop and apply a gradient-boosting model and an analog ensemble approach to temporally extrapolate such uncertainty to the full 20-year period, for which only a single model run is available. As a test case, we consider offshore wind resource characterization in the California Outer Continental Shelf. Both of the proposed approaches provide accurate estimates of the long-term wind speed boundary condition and parametric uncertainty across the region (R 2 >0.75), with the gradient-boosting model slightly outperforming the analog ensemble in terms of bias and centered root-mean-square error. At the three offshore wind energy lease areas in the region, we find a long-term median hourly uncertainty between 10 % and 14 % of the mean hub-height wind speed values. Finally, we assess the physical variability in the uncertainty estimates. In general, we find that the wind speed uncertainty increases closer to land. Also, neutral conditions have smaller uncertainty than the stable and unstable cases, and the modeled wind speed in winter has less boundary condition and parametric sensitivity than summer.

17 WIND ENERGY↗

Offshore low-level jet observations and model representation using lidar buoy data off the California coast

Abstract. Low-level jets (LLJs) occur under a variety of atmospheric conditions and influence the available wind resource for wind energy projects. In 2020, lidar-mounted buoys owned by the US Department of Energy (DOE) were deployed off the California coast in two wind energy lease areas administered by the Bureau of Ocean Energy Management: Humboldt and Morro Bay. The wind profile observations from the lidars and collocated near-surface meteorological stations (4–240 m) provide valuable year-long analyses of offshore LLJ characteristics at heights relevant to wind turbines. At Humboldt, LLJs were associated with flow reversals and north-northeasterly winds, directions that are more aligned with terrain influences than the predominant northerly flow. At Morro Bay, coastal LLJs were observed primarily during northerly flow as opposed to the predominant north-northwesterly flow. LLJs were observed more frequently in colder seasons within the lowest 250 m a.s.l. (above sea level), in contrast with the summertime occurrence of the higher-altitude California coastal jet influenced by the North Pacific High, which typically occurs at heights of 300–400 m. The lidar buoy observations also validate LLJ representation in atmospheric models that estimate potential energy yield of offshore wind farms. The European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) was unsuccessful at identifying all observed LLJs at both buoy locations within the lowest 200 m. An extension of the National Renewable Energy Laboratory (NREL) 20-year wind resource dataset for the Outer Continental Shelf off the coast of California (CA20-Ext) yielded marginally greater captures of observed LLJs using the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary layer (PBL) scheme than the 2023 National Offshore Wind dataset (NOW-23), which uses the Yonsei University (YSU) scheme. However, CA20-Ext also produced the most LLJ false alarms, which are instances when a model identified an LLJ but no LLJ was observed. CA20-Ext and NOW-23 exhibited a tendency to overestimate the duration of LLJ events and underestimate LLJ core heights.

17 WIND ENERGY↗

Information Searching in the Residential Solar PV Market

This paper examines the consumer information search behavior of households in San Diego County with solar photovoltaic (PV) systems. We focus on whether solar PV households financing the technology through third-party ownership (TPO) versus host-ownership (HO), which is equivalent to leasing or buying goods in other markets, have heterogeneous preferences as reflected by information search. Conditional on adoption, we find that TPO households tend to seek more information on home modifications required for solar installation whereas HO households seek more information on the financial returns of solar investments. These preferences may be correlated with the consumption of other goods and services, and thus, if used to inform marketing strategies, our results could help reduce solar PV customer acquisition costs and accelerate technology diffusion. They also have indirect implications for marketing goods and services in other contexts where consumers exhibit similar preferences.

California↗