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Title: What can surface wind observations tell us about interannual variation in wind energy output?

Abstract

The past decade of wind power growth was supported by capacity factor improvements and associated cost reductions. But are higher capacity factors a technology success story or, as suggested by recent research, has the influence of technology been overstated by ignoring positive surface wind speed trends? The answer could influence estimates of wind energy's cost and even future deployment rates. We find that US surface wind speed observations imply a 2.6% improvement in capacity factors from 2010 to 2019. Yet newer vintages of wind plants have recorded capacity factors that are ~25% larger than plants built close to 2010. It follows that technological factors and improved site quality, not higher wind speeds, drove most of the improvement in capacity factors. Additionally, we match hundreds of meteorological stations to nearby (< 25 km) wind plants and compare annual estimated generation, based on a function of surface wind speed observations, to annual recorded generation. Researchers rely on this publicly available surface data because measurements co-located with wind plants are generally considered proprietary. Our analysis addresses a research gap: interannual variation in observed surface wind speeds is rarely compared to observed data at wind plant locations and turbine heights. We find that despitemore » its common use for this purpose, generation estimates based on publicly available surface observational data provide a poor proxy for interannual variability in recorded wind generation. These findings suggest that caution is generally needed when researchers use surface wind speed measurements to investigate long-term wind energy trends.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Laboratory Berkeley California USA
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office
OSTI Identifier:
1846956
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Wind Energy
Additional Journal Information:
Journal Volume: 25; Journal Issue: 6; Journal ID: ISSN 1095-4244
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; capacity factor; surface wind observations

Citation Formats

Millstein, Dev, Bolinger, Mark, and Wiser, Ryan. What can surface wind observations tell us about interannual variation in wind energy output?. United States: N. p., 2022. Web. doi:10.1002/we.2717.
Millstein, Dev, Bolinger, Mark, & Wiser, Ryan. What can surface wind observations tell us about interannual variation in wind energy output?. United States. https://doi.org/10.1002/we.2717
Millstein, Dev, Bolinger, Mark, and Wiser, Ryan. Tue . "What can surface wind observations tell us about interannual variation in wind energy output?". United States. https://doi.org/10.1002/we.2717. https://www.osti.gov/servlets/purl/1846956.
@article{osti_1846956,
title = {What can surface wind observations tell us about interannual variation in wind energy output?},
author = {Millstein, Dev and Bolinger, Mark and Wiser, Ryan},
abstractNote = {The past decade of wind power growth was supported by capacity factor improvements and associated cost reductions. But are higher capacity factors a technology success story or, as suggested by recent research, has the influence of technology been overstated by ignoring positive surface wind speed trends? The answer could influence estimates of wind energy's cost and even future deployment rates. We find that US surface wind speed observations imply a 2.6% improvement in capacity factors from 2010 to 2019. Yet newer vintages of wind plants have recorded capacity factors that are ~25% larger than plants built close to 2010. It follows that technological factors and improved site quality, not higher wind speeds, drove most of the improvement in capacity factors. Additionally, we match hundreds of meteorological stations to nearby (< 25 km) wind plants and compare annual estimated generation, based on a function of surface wind speed observations, to annual recorded generation. Researchers rely on this publicly available surface data because measurements co-located with wind plants are generally considered proprietary. Our analysis addresses a research gap: interannual variation in observed surface wind speeds is rarely compared to observed data at wind plant locations and turbine heights. We find that despite its common use for this purpose, generation estimates based on publicly available surface observational data provide a poor proxy for interannual variability in recorded wind generation. These findings suggest that caution is generally needed when researchers use surface wind speed measurements to investigate long-term wind energy trends.},
doi = {10.1002/we.2717},
journal = {Wind Energy},
number = 6,
volume = 25,
place = {United States},
year = {Tue Feb 08 00:00:00 EST 2022},
month = {Tue Feb 08 00:00:00 EST 2022}
}

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