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The future of wind energy in California: Future projections with the Variable-Resolution CESM

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  • Wang, Meina
  • Ullrich, Paul
  • Millstein, Dev

Abstract

Shifting wind patterns are an expected consequence of global climate change, with direct implications for wind energy production. However, wind is notoriously difficult to predict, and significant uncertainty remains in our understanding of climate change impacts on existing wind generation capacity. In this study, historical and future wind climatology and associated capacity factors at five wind turbine sites in California are examined. Historical (1980–2000) and mid-century (2030–2050) simulations were produced using the Variable-Resolution Community Earth System Model (VR-CESM) to understand how these wind generation sites are expected to be impacted by climate change. A high-resolution statistically downscaled WRF product provided by DNV GL, reanalysis datasets MERRA-2, CFSR, NARR, and observational data were used for model validation and comparison. These projections suggest that wind power generation capacity throughout the state is expected to increase during the summer, and decrease during fall and winter, based on significant changes at several wind farm sites. This study improves the characterization of uncertainty around the magnitude and variability in space and time of California's wind resources in the near future, and also enhances our understanding of the physical mechanisms related to the trends in wind resource variability.

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  • Wang, Meina & Ullrich, Paul & Millstein, Dev, 2018. "The future of wind energy in California: Future projections with the Variable-Resolution CESM," Renewable Energy, Elsevier, vol. 127(C), pages 242-257.
    • Handle: RePEc:eee:renene:v:127:y:2018:i:c:p:242-257
    DOI: 10.1016/j.renene.2018.04.031
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    References listed on IDEAS

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    Cited by:

    1. Jung, Christopher & Schindler, Dirk, 2022. "A review of recent studies on wind resource projections under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    2. Markus Gross & Vanesa Magar & Alfredo Peña, 2020. "The Effect of Averaging, Sampling, and Time Series Length on Wind Power Density Estimations," Sustainability, MDPI, vol. 12(8), pages 1-13, April.
    3. Quetzalcoatl Hernandez-Escobedo & Javier Garrido & Fernando Rueda-Martinez & Gerardo Alcalá & Alberto-Jesus Perea-Moreno, 2019. "Wind Power Cogeneration to Reduce Peak Electricity Demand in Mexican States Along the Gulf of Mexico," Energies, MDPI, vol. 12(12), pages 1-22, June.
    4. Chen, Liang, 2020. "Impacts of climate change on wind resources over North America based on NA-CORDEX," Renewable Energy, Elsevier, vol. 153(C), pages 1428-1438.

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