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

被引:2
|
作者
Millstein, Dev [1 ]
Jeong, Seongeun [1 ]
Ancell, Amos [1 ]
Wiser, Ryan [1 ]
机构
[1] Lawrence Berkeley Natl Lab, Energy Anal & Environm Impacts Div, Berkeley, CA 94720 USA
关键词
FARM FLOW-CONTROL; REANALYSIS; SOLAR; ASSIMILATION; PERFORMANCE; STRATEGIES; DATASET; OUTPUT; ERA5;
D O I
10.1038/s41597-023-02804-w
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In 2022, wind generation accounted for similar to 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.
引用
收藏
页数:15
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