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The dataset contains raw data from NREL's profiling lidar (Windcube v2.1) at AWAKEN site B. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution.
The purpose of this dataset is to provide preliminary filtered, averaged lidar data and standardize the data format of various datastreams from the buoy into NetCDF.
The purpose of this dataset is to provide preliminary filtered, averaged lidar data and to standardize the data format of various datastreams from the buoy into NetCDF.
Fraunhofer IWES's profiling lidar (Windcube v2.0) raw data at AWAKEN site D. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution.
This dataset contains raw data from NREL's profiling lidar (Windcube v2.1) at AWAKEN site A1. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution.
This dataset contains raw data from the profiling lidar (Windcube v2.1) at AWAKEN site A2. Two data types are included here: 1) STA files, which have 10-minute average data, and 2) RTD files, which have real time data, at about 1 Hz resolution.
This dataset contains processed data from the upgraded Galion lidar at the RHOD site.
These data include scanning Doppler lidar measurements from the deployment of the PNNL HALO XR+ (s/n 184) at the Nantucket site. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate. The data are provided in NetCDF.
This dataset consists of netCDF files containing L1 data from the WHOI ceilometer at Woods Hole.
This dataset contains vertical profiling lidar data from AWAKEN site A1. This is the ZephIR300 #773 lidar system. The .csv files are monthly data files with 10-min average data. The .zip files are daily high frequency data and zipped by month.
This dataset contains processed NREL thermodynamic profiler (Assist II-12) data from the WFIP3 CACO site.
This dataset contains reviewed data from the WFIP3 Laser Disdrometer.
Long-range scanning Doppler lidar located on Gordon Ridge. The WindTracer provides high-resolution, long-range lidar data for use in the WFIP2 program.
The American Wind Wildlife Institute (AWWI – now Renewable Energy Wildlife Institute, REWI) – was appointed prime awardee of DOE award number DE-EE0007880 to lead a team of scientists, wind developers, and technology manufacturers in a collaborative evaluation of the effectiveness of a technology intended to help reduce eagle collisions with wind turbines. IdentiFlight, developed by Renewable Energy Systems (RES) in collaboration with Boulder Imaging, is an autonomous aerial monitoring and detection system. REWI partnered with ecological consultants, Western Ecosystems Technology, Inc. (WEST), to independently evaluate the performance of IdentiFlight reducing eagle collision risk under a suite of environmental conditions relative to the performance of a Biomonitor (human observer-based) Program. The project objectives were to 1) evaluate how IdentiFlight compared to biomonitors in detecting and identifying eagles under a suite of environmental conditions and 2) use the observation data to model how IdentiFlight and biomonitors reduced the eagle fatality prediction through informed curtailment. Field testing was to take place at two geographically distinct wind farms over two field seasons at each wind farm with a study design appropriate for meta-analyses across sites and years.
This dataset contains streamwise velocity retrieved from the Range Height Indicator (RHI) scans done by the UC Davis scanning Lidar. The quality control of the radial wind speed is performed following the algorithm of Beck & Kuhn (2017). Instantaneous realizations characterized by wind misalignment greater than 60 degrees (based on the closest VAD scan in time) are discarded.
Power Purchase Agreements (PPAs) are becoming increasingly preferred among large energy consumers, such as data centers, to secure cost-effective energy and meet accelerating demand growth. Traditionally, variable renewable energy (VRE)-based PPAs operate on a pay-as-produced basis, balancing supply and demand for a relatively longer duration (e.g., annually). However, the focus is shifting toward matching supply and demand on an hourly basis to fully meet energy needs. This shift requires the integration of flexible energy resources, such as hydropower, thermal generation, and energy storage, to complement VRE sources like wind and solar, forming the foundation for 24/7 PPA. This work contributes by: (i) reviewing emerging market trends and current practices in PPA procurement, supported by data on PPA prices and technology portfolios; (ii) synthesizing the existing literature on modeling approaches for contract pricing, quantities, hybrid resource procurement, and risk management in 24/7 PPA design, while identifying key research gaps; and (iii) proposing an integrated 24/7 PPA design framework along with two contracting mechanisms from the perspectives of both PPA providers and consumers. The proposed framework highlights critical modeling challenges, risk-allocation issues, and future research opportunities for 24/7 PPA design.
The American WAKE ExperimeNt (AWAKEN) collaboration is an observational-based field campaign in northern Oklahoma intended to analyze the potential influence of onshore wind farms and their collective wakes on wind power production, turbine structural loads, and on the atmospheric boundary layer (ABL). Focusing on the ABL effects, the University of Oklahoma and the Lawrence Livermore National Laboratory collected continuous high-resolution kinematic and thermodynamic profile measurements during 2022 and Summer 2023. The deployment strategy for these campaigns is detailed first, followed by an initial comparison of data from two sites in the AWAKEN domain: a near-farm site to examine collective wake impacts on the ABL, and a far-field site remaining outside the wind farm-waked region. Here, we summarize the datasets available and demonstrate the benefits of these observations and multiple value-added products (VAPs) for investigation of ABL features observed during AWAKEN. We also highlight examples of preliminary analyses, including ABL height detection and nocturnal low-level jet examination, which are produced using novel VAPs based on optimal estimation to retrieve deeper Doppler lidar wind profiles than previously resolved, along with their uncertainty. By including the near-farm and far-field site in these analyses, we identified a pattern of stronger lower-atmospheric mixing at the near-farm site than the far-field site, motivating deeper investigation into the relationship between wind farms and general ABL characteristics. Future analysis will delve deeper into this relationship by examining other ABL characteristics, such as atmospheric stability and convection.