Distributed Wind Resource Assessment Workshop

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Through the U.S. Department of Energy’s Request for Information: Acceleration of Distributed Generation from Wind Energy Systems,[1] wind resource assessment was identified as a technical focus area for distributed wind research. Accurate wind resource assessment is critical to the success of the distributed wind market in the United States and has implications for energy production, reliability, profitability, and levelized cost of energy. The National Renewable Energy Laboratory organized a wind resource assessment stakeholder workshop on June 18-19, 2015, in Stevens Point, Wisconsin, to further explore the challenges and opportunities in this technical focus area. The expected outcome of this workshop is a report identifying the current state of technology, research and development challenges and barriers, and challenges that if solved have a high pay-off.

Workshop Purpose

Bring together experts and stakeholders to share the current status of tools and approaches for wind resource assessment in distributed wind applications.

Workshop Goals

  • Achieve input and participation from wind industry representatives on the present state of the art for distributed wind resource assessment
  • Generate common definitions and understanding for the wind resource assessment process that will be useful in helping the industry advance
  • Understand the wind resource assessment capabilities of the distributed wind industry by gathering data, identifying strengths and weaknesses
  • Cross-pollinate information and techniques from different sectors of the industry.

Workshop Objective

Obtain insight into industry concerns for wind resource assessment specific to distributed wind technology development and deployment.

Panel Session #1: Industry Baseline Methods Development

With a focus on baselining and categorizing wind resource methods by sector (small, medium, community, and utility-scale wind), this session included discussions of power production estimation methods, site suitability methodologies, and a gaps analysis (what are the gaps for current methods on power estimation and site suitability?).

Panel chair:

Speakers and panelists:

Panel Session #2: Accuracy and Uncertainty of Wind Resource Assessment Methods by Sector

This session included presentations demonstrating, through empirical data, the accuracy of the baseline methods.

Panel chair:

  • David Willy, Northern Arizona University

Speakers and panelists:

Panel Session #3: Opportunities for Improved Resource Assessment

This panel highlighted current limitations in the approaches for wind resource assessment and opportunities for improvement with instrumentation and models. Panel members also discussed the technical goals for such improvements, including wind speed accuracy, costs, and time durations. These goals were used by the breakout groups to assess opportunities in their respective spaces.

Panel chair:

  • Mia Devine, NW SEED

Speakers and panelists:

Workshop Outcomes

Workshop participants identified the following challenges and barriers:

  • Accuracy of the current approach is low and generally inconsistent
  • Lack of publically available and low-cost data/tools
  • Little verification of existing tools/rules of thumb
  • Lack of standards in processes and documentation
  • Industry relies heavily on personal experience; limited training and educational opportunities
  • Limited funding or processes to understand errors or improve assessment process – limited feedback loop
  • Poor understanding of the cost/benefit of different fidelities of wind resource assessment (on-site data collection, model selection)
  • Limited feedback between OEMs and site assessors – lack of an ability to do more detailed site optimization
  • Total wind resource assessment costs (dollars and effort) must be tiered to reflect project size and volume.

Workshop participants identified the following areas in which efforts should be focused:

  • Improve data access and availability
  • Conduct education and outreach
  • Validate and benchmark model and process
  • Improve scaling methods and data assumptions
  • Standardize processes and reporting
  • Develop low-cost instrumentation, measurement systems, and data processing
  • Streamline and automate model input to allow easier use of existing and future models.


  1.  "U.S. Department of Energy. Request for Information: Acceleration of Distributed Generation from Wind Energy Systems"