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  1. Research
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  4. Wind Energy
  5. Wind Resource Characterization

Wind Resource Characterization

Characterizing wind for forecasting accuracy

PNNL has modeling, instrumentation, and data management expertise to improve accuracy of wind forecasts.

Shannon Colson, PNNL

  • Solar Energy
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Before energy operators build wind plants, they need confidence that they can supply a sufficient stream of clean, low-cost wind energy to business and home owners. For that confidence, they need a better idea of when the wind will blow, how strongly, and with what variability. Once a wind plant begins operation, operators also need accurate forecasts for managing their production relative to wind energy markets. 

The Department of Energy (DOE) Wind Energy Technologies Office (WETO) is helping to give industry the confidence it needs through collaborative research conducted among DOE’s national laboratories, industry, and academia which provides a better understanding of the wind plant operating environment. 

PNNL manages two lidar buoys for offshore wind resource characterization. Using atmospheric and oceanographic measurement capabilities, the lidar buoys capture data such as wind speed and direction at multiple heights using wind profiling lidar, air and sea surface temperatures, ocean current speeds and directions, and wave heights and directions. The centerpiece instrument on each buoy is a wind profiling lidar that provides wind information up to 250 meters above the sea surface—where offshore wind turbines would be located. In 2020, the lidars received an independent performance validation documenting that the offshore lidars received Stage 2 (pre-commercial) certification in compliance with the recommended practices of the International Energy Agency (IEA) Wind Technology Collaboration Programme. The collection and dissemination of buoy data for the benefit of the public and industry is critical to the program. Data obtained from lidar buoy deployments are stored in Wind Data Hub, which is managed by PNNL data management and computer scientists. 

As part of the Observationally driven Resource Assessment with CoupLEd models project, or ORACLE, PNNL is increasing the trust in novel observational algorithms and ocean-wave-atmosphere modeling techniques to reduce uncertainty for offshore wind energy along the U.S. West Coast.  To achieve this, the team of researchers are creating an observational database of ground-based and satellite data across the nation’s west coast and developing a multi-year wind-wave simulations observatory to study air-sea interactions. Additionally, the project evaluates the impact of clouds, precipitation, and climate change on offshore wind energy off U.S. West Coast.

PNNL is part of a group of national laboratories that will play a role in American WAKE ExperimeNt—or AWAKEN—campaign. AWAKEN, which also engages multiple federal agencies as well as research groups outside the United States, is designed to gather observational and model data to address questions about wind turbine wake interactions and aerodynamics and to further understand wake behavior and validate wind plant models. The campaign is taking place in the nation’s Midwest, where wind plant growth is significant. The data resulting from these and other studies supported by WETO are stored and publicly available through PNNL’s Wind Data Hub.

Recent News

JUNE 1, 2020
Feature

Tip the Cap to the DAP: Managing DOE’s Wind Data Portal

Read
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OCTOBER 30, 2018
Feature

Oh Buoy! PNNL Researchers Dive into Data Delivered from New Jersey Coast

Read
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MAY 14, 2018
Feature

DOE-Funded Wind Profilers Feed National Weather Forecasts

Read
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Related Divisions

Earth Systems Science Division
Atmospheric Sciences and Global Change Division
Advanced Computing, Mathematics, and Data
Coastal Sciences Division

Contacts

Alicia M. Mahon, Ph.D., PMP
Wind Energy Program Manager, Offshore Wind and Ocean Dynamics Team Leader
alicia.mahon@pnnl.gov
509-375-6943
Raghavendra (Raghu) Krishnamurthy
Earth scientist, Wind Resource Characterization portfolio manager
raghavendra.krishnamurthy@pnnl.gov

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