Preprints
https://doi.org/10.5194/wes-2022-14
https://doi.org/10.5194/wes-2022-14
 
22 Mar 2022
22 Mar 2022
Status: this preprint is currently under review for the journal WES.

Optimization of wind farm portfolio to minimize the overall power fluctuations – a case study for the Faroe Islands

Turið Poulsen1, Bárður A. Niclasen1, Gregor Giebel2, and Hans Georg Beyer1 Turið Poulsen et al.
  • 1Faculty of Science and Technology, University of the Faroe Islands
  • 2Department of Wind Energy, Technical University of Denmark

Abstract. Hourly modeled wind turbine power output time series – modeled from outputs from the mesoscale numerical weather prediction system WRF – are used to examine the spatial smoothing of various wind farm portfolios located on a complex isolated island group with a surface area of 1400 km2. Power spectral densities (PSD), hourly step change functions, and duration curves are generated, and the 5th and 95th percentiles of the step change functions are calculated. The spatial smoothing is identified from smaller high frequency PSD values, less hourly fluctuations, and more flat duration curves per installed wind power capacity, compared to single wind turbine outputs. A discussion on the limitation of the spatial smoothing for the region is included, where a smoothing effect is clear for periods up to 1–2 days, although most evident at the higher frequencies. By maximizing the smoothing effect, optimal wind farm portfolios are presented with the intention to minimize the overall wind power fluctuations. The focus is mainly on the smoothing effect in highest resolvable frequencies. Optimizing wind farm capacities at fourteen pre-defined good wind farm site locations has a minimal improvement on the hourly fluctuations. However, choosing good combinations of the individual wind farm site locations decrease the 1–3 hourly fluctuations considerably; the optimized wind farm portfolios consist of distant wind farms, while poor portfolios consist of clustered wind farms. The 5th and 95th percentiles are 15 % less for an optimized portfolio with four wind farms compared to a poor combination of four wind farms.

Turið Poulsen et al.

Status: open (until 23 Jun 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Turið Poulsen et al.

Turið Poulsen et al.

Viewed

Total article views: 188 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
141 43 4 188 2 3
  • HTML: 141
  • PDF: 43
  • XML: 4
  • Total: 188
  • BibTeX: 2
  • EndNote: 3
Views and downloads (calculated since 22 Mar 2022)
Cumulative views and downloads (calculated since 22 Mar 2022)

Viewed (geographical distribution)

Total article views: 172 (including HTML, PDF, and XML) Thereof 172 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 20 May 2022
Download
Short summary
Wind power is cheap and environmentally friendly. But it has a disadvantage, it is a variable power source. Because wind is not blowing everywhere simultaneously, optimal placement of wind farms can reduce the fluctuations. This is explored further for a small isolated area. Combining wind farms reduces wind power flucutations for time scales up to 1–2 days. By optimally placing four wind farms, the extreme hourly fluctuations are reduced by 15 %, with wind farms located distant from each other.