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Introducing a new wind speed complementarity model

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  • Jung, Christopher
  • Schindler, Dirk

Abstract

Minimizing the residual load is essential in countries with a high share of variable renewable energies (VRE). Optimally, new wind turbine sites provide high resource availability and the potential for smoothing the temporal course of the residual load. Current high spatial resolution wind atlases are limited to the ability to find high capacity factor (CF) sites but do not provide CF during periods of high residual load. Thus, we derive a new high-spatiotemporal resolution wind speed model for adjusting wind turbine site selection to residual load. The model (WiCoMo) is developed at six-hourly temporal resolution and 25 m × 25 spatial resolution up to 200 m height from 1991 to 2018 in the study area of Germany. Residual load-weighted and adjusted CF in 2015–2018 is mapped using the new model and considering the national residual load. Besides, complementarity between CF and VRE is evaluated. According to the standard CF, there is a northwest-southeast CF gradient. Relying on the residual load adjusted CF site suitability in southern Germany increases compared to the rest of the country. The introduced model may be a valuable tool for adapting wind resource assessment in Germany on the increasing role of VRE in the electricity mix.

Suggested Citation

  • Jung, Christopher & Schindler, Dirk, 2023. "Introducing a new wind speed complementarity model," Energy, Elsevier, vol. 265(C).
    • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s036054422203170x
    DOI: 10.1016/j.energy.2022.126284
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    Cited by:

    1. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2024. "Prediction of hourly wind speed time series at unsampled locations using machine learning," Energy, Elsevier, vol. 299(C).

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