Impacts of climate change on wind energy power – Four wind farms in Spain

Solaun, Kepa; Cerdá, Emilio

doi:10.1016/j.renene.2019.06.129

Cited by 60 publications

(23 citation statements)

References 34 publications

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“…The near-surface wind speed (NWS) is a critical index with which to quantify wind resource potential. However, climate change can directly influence the spatiotemporal distribution and quality (or output) of wind energy [2,3]. Furthermore, changes in NWS associated with the increasing frequency and intensity of extreme weather events, resulting from climate change, could be detrimental to the operation of wind farms and cause uncertainty regarding the use of renewable energy sources [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

Deng

Hua

Fan³

2021

Atmosphere

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The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100).

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Section: Introductionmentioning

confidence: 99%

Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models

Deng

Hua

Fan³

2021

Atmosphere

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“…Because of this reason, wind power plants should be planned and designed with care. The pay-off period is going to be longer than expected while planning [38,39]. The current investigation shows that the best region for wind power plant building in Lithuania is the coastal area, where a wind speed increase was projected.…”

Section: Discussionmentioning

confidence: 80%

Projected Near-Surface Wind Speed Trends in Lithuania

Jankevičienė

Kanapickas

2021

Energies

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Developing wind energy in Lithuania is one of the most important ways to achieve green energy goals. Observational data show that the decline in wind speeds in the region may pose challenges for wind energy development. This study analyzed the long-term variation of the observed 2006–2020 and projected 2006–2100 near-surface wind speed at the height of 10 m over Lithuanian territory using data of three models included in the Coupled Model Intercomparison Project phase 5 (CMIP5). A slight decrease in wind speeds was found in the whole territory of Lithuania for the projected wind speed data of three global circulation models for the scenarios RCP2.6, RCP4.5, and RCP8.5. It was found that the most favorable scenario for wind energy production is RCP2.6, and the most unfavorable is the RCP4.5 scenario under which the decrease in wind speed may reach 12%. At the Baltic Sea coastal region, the decline was smaller than in the country’s inner regions by the end of the century. The highest reduction in speed is characteristic of the most severe RCP8.5 scenario. Although the analysis of wind speeds projected by global circulation models (GCM) confirms the downward trends in wind speeds found in the observational data, the projected changes in wind speeds are too small to significantly impact the development of wind farms in Lithuania.

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“…Wind speed is not expected to have meaningful variations in the upcoming decades (data not shown). Solaun and Cerdá (2020) have shown an increase in wind speed near surface during warming scenarios occurring in other countries, but these studies usually simulate wind speed at 10 m height or higher and have larger timeframes. Rainfall is expected to increase during the wet season and to decrease during the dry season in most locations in northeastern Pará, in the coming decades.…”

Section: Predicted Changes In Climatementioning

confidence: 99%