4.8 Article

Validation of European-scale simulated wind speed and wind generation time series

期刊

APPLIED ENERGY
卷 305, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2021.117794

关键词

Large scale energy system; Wind energy; Atmospheric reanalysis; European; Renewable energy; Wind generation; Validation

资金

  1. The Low-Wind turbine concept for optimal system integration'' (Danish Energy Agency) [EUDP2019-I, 64019-0074]
  2. ForskEL/EUDP OffshoreWake project [PSO-12521]
  3. DTU Wind Energy PSfuture (La Cour Fellowship)
  4. European Commission (EC) [FP7ENERGY.2013.10.1.2]
  5. Danish Energy Agency (Denmark) [64014-0590, EUDP 14-II]

向作者/读者索取更多资源

This study validates atmospheric reanalysis data sets for simulating onshore wind generation time series for large-scale energy system studies. The results show that the mean wind speed scaling is necessary to match the distribution of generation at the country level, with NEWA-GWA2 and ERA5-GWA2 showing the highest accuracy and precision for simulating large-scale wind generation.
This paper presents a validation of atmospheric reanalysis data sets for simulating onshore wind generation time series for large-scale energy system studies. The three reanalyses are the ERA5, the New European Wind Atlas (NEWA) and DTU's previous generation European-level atmospheric reanalysis (EIWR). An optional scaling is applied to match the microscale mean wind speeds reported in the Global Wind Atlas version 2 (GWA2). This mean wind speed scaling is used to account for the effects of terrain on the wind speed distributions. The European wind power fleet for 2015-2018 is simulated, with commissioning of new wind power plants (WPPs) considered for each year. A generic wake model is implemented to include wake losses that are layout agnostic; the wake model captures the expected wake losses as function of wind speed given the technical characteristics of the WPP. We validate both point measurement wind speeds and generation time-series aggregated at the country-level. Wind measurements from 32 tall meteorological masts are used to validate the wind speed, while power production for four years from twelve European countries is used to validate the simulated country-level power production. Various metrics are used to rank the models according to the variables of interest: descriptive statistics, distributions, daily patterns, auto-correlation and spatial correlation. We find that NEWA outperforms ERA5 and EIWR for the simulated wind speed, but, as expected, no model is able to fully describe the auto-correlation function of the wind speed at a single point. The mean wind speed scaling is found to be necessary to match the distribution of generation on country-level, with NEWA-GWA2 and ERA5-GWA2 showing highest accuracy and precision for simulating large-scale wind generation time-series.

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