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Data-driven mapping of hourly wind speed and its potential energy resources: A sensitivity analysis

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  • Collados-Lara, Antonio-Juan
  • Baena-Ruiz, Leticia
  • Pulido-Velazquez, David
  • Pardo-Igúzquiza, Eulogio

Abstract

Renewable energies play a significant role to mitigate the impacts of climate change. In countries like Spain, there is a significant potential of wind energy production which might be a key resource. In this research, we obtain wind power at 80 m height and wind turbine energy (assuming a specific turbine). To achieve this objective we produce an optimal mapping of the hourly “instantaneous surface wind speed” (height 10 m), based on the available data. An extensive region (Granada Province, south Spain) is studied with a spatial resolution of 300 m, during a long period (1996–2016). It allows us to assess the intra- and inter-daily variability of wind energy resources. Several interpolation approaches are tested and a cross validation experiment is applied to identify the optimal approach. The obtained maps were compared with the results obtained in the stations with two common frequency distributions (Rayleigh and Weibull). This is the first time that this sensitivity integrated analysis is performed over an extensive region (12600 km2) for a long time period (20 years) at fine spatiotemporal resolution (300 m, hourly scale). The results can be very valuable for a preliminary analysis of potential optimal location of wind energies facilities.

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  • Collados-Lara, Antonio-Juan & Baena-Ruiz, Leticia & Pulido-Velazquez, David & Pardo-Igúzquiza, Eulogio, 2022. "Data-driven mapping of hourly wind speed and its potential energy resources: A sensitivity analysis," Renewable Energy, Elsevier, vol. 199(C), pages 87-102.
  • Handle: RePEc:eee:renene:v:199:y:2022:i:c:p:87-102
    DOI: 10.1016/j.renene.2022.08.109
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