A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Millstein, Dev; Jeong, Seongeun; Ancell, Amos; Wiser, Ryan

doi:10.1038/s41597-023-02804-w

Title: A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

Journal Article · Fri Dec 08 00:00:00 UTC 2023 · Scientific Data

DOI: https://doi.org/10.1038/s41597-023-02804-w · OSTI ID:2229194

; Jeong, Seongeun;

; Wiser, Ryan

Abstract In 2022, wind generation accounted for ~10% of total electricity generation in the United States. As wind energy accounts for a greater portion of total energy, understanding geographic and temporal variation in wind generation is key to many planning, operational, and research questions. However, in-situ observations of wind speed are expensive to make and rarely shared publicly. Meteorological models are commonly used to estimate wind speeds, but vary in quality and are often challenging to access and interpret. The Plant-Level US multi-model WIND and generation (PLUSWIND) data repository helps to address these challenges. PLUSWIND provides wind speeds and estimated generation on an hourly basis at almost all wind plants across the contiguous United States from 2018–2021. The repository contains wind speeds and generation based on three different meteorological models: ERA5, MERRA2, and HRRR. Data are publicly accessible in simple csv files. Modeled generation is compared to regional and plant records, which highlights model biases and errors and how they differ by model, across regions, and across time frames.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2229194

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 10; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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Title: A database of hourly wind speed and modeled generation for US wind plants based on three meteorological models

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