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DOE OSTI · 1760659

Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates

Duplyakin, Dmitry·Zisman, Sagi·Phillips, Caleb·Tinnesand, Heidi
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Abstract

Much like their counterparts in utility-scale wind energy, developers of industrial, small-scale and distributed wind turbine deployments need to understand and accurately characterize the wind resource to properly assess the power generation and financial ramifications during siting and planning. National Renewable Energy Laboratory’s WIND (Wind Integration National Dataset) Toolkit (WTK) provides a best-in-class wind resource dataset generated using the Weather Research and Forecasting (WRF) model. This dataset includes parameters such as the wind speed, wind direction, and temperature at various heights, plus atmospheric stability near the surface. This data is available at 2-km spatial resolution and five-minute temporal resolution across 7 years, from 2007 to 2013 through a publicly accessible API interface. The Tools Assessing Performance (TAP) project seeks to extend this dataset to allow long term resource estimates and leverage it to better equip distributed wind equipment manufacturers, owner-operators, and installation professionals with better tools for practical siting applications. In this report, we present the results from our investigation within the TAP project focused on characterization of bias in WTK-based wind speed estimates and evaluation of vertical and horizontal interpolation techniques. We discuss the tradeoffs between different techniques and their combinations, as well as describe the lower bounds we determine for the studied validation errors. While the specific estimates we present are specific to WTK and the validation dataset we have chosen for this investigation (NREL's Wind Resource Meteorological Database), the overall analysis and the studied techniques are general enough to be applied to a broader set of wind datasets, both simulation-based and observational.

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17 WIND ENERGYdistributed wind sitinghorizontal interpolationvertical interpolationWind Integration National Dataset (WIND) ToolkitWind Resource Meteorological Databasewind speed estimate validation

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Duplyakin, Dmitry, Zisman, Sagi, Phillips, Caleb, Tinnesand, Heidi. 2021-01-01. Bias Characterization, Vertical Interpolation, and Horizontal Interpolation for Distributed Wind Siting Using Mesoscale Wind Resource Estimates. https://doi.org/10.2172/1760659

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