Preprints
https://doi.org/10.5194/wes-2022-33
https://doi.org/10.5194/wes-2022-33
 
04 May 2022
04 May 2022
Status: this preprint is currently under review for the journal WES.

Evaluating the mesoscale spatio-temporal variability in simulated wind speed time series over Northern Europe

Graziela Luzia, Andrea Noemi Hahmann, and Matti Juhani Koivisto Graziela Luzia et al.
  • Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark

Abstract. As wind energy increases its share of total electricity generation and its integration into the power system becomes more challenging, accurately representing the spatio-temporal variability in wind data becomes crucial. Wind fluctuations impact power and energy systems, e.g., energy system planning, vulnerability to storm shutdowns, and available voltage stability support. To analyze such fluctuations and their spatio-temporal dependencies, time series of wind speeds at hourly time-frequency or higher are needed. We provide a comprehensive evaluation of the global and mesoscale-model derived wind time series against observations by using a set of metrics that we present as requirements for wind energy integration studies. We also perform a sensitivity analysis to find the best model setup of the Weather Research and Forecasting (WRF) model, focusing on evaluating the wind speed fluctuation metrics. The results show that using higher spatial resolution in the WRF model simulations improves the representation of temporal fluctuations; however, higher-resolution simulations often lower the correlations of wind time series with measurements. We also show that the nesting strategy is an important consideration, and a smoother transition from the forcing data to the nested domains improves the correlations with measurements. All mesoscale model simulations overestimate the value of the spatial correlations in wind speed with respect to their observed values. Still, the spatial correlations and the wind speed distributions are insensitive to the model configuration tested in this study.

Graziela Luzia et al.

Status: open (until 22 Jun 2022)

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Graziela Luzia et al.

Graziela Luzia et al.

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Short summary
This paper presents a comprehensive validation of time series produced by a mesoscale numerical weather model, a global reanalysis, and a wind atlas against observations by using a set of metrics that we present as requirements for wind energy integration studies. We perform a sensitivity analysis on the numerical weather model in multiple configurations, such as related to model grid spacing and nesting arrangements, to define one model setup that outperforms in various time series aspects.