Spatiotemporal correlations in the power output of wind farms: On the impact of atmospheric stability

Nicolas Tobin, Adam Lavely, Sven Schmitz, Leonardo P. Chamorro

Research output: Contribution to journalArticle

Abstract

The dependence of temporal correlations in the power output of wind-turbine pairs on atmospheric stability is explored using theoretical arguments and wind-farm large-eddy simulations. For this purpose, a range of five distinct stability regimes, ranging from weakly stable to moderately convective, were investigated with the same aligned wind-farm layout used among simulations. The coherence spectrum between turbine pairs in each simulation was compared to theoretical predictions. We found with high statistical significance (p < 0.01) that higher levels of atmospheric instability lead to higher coherence between turbines, with wake motions reducing correlations up to 40%. This is attributed to higher dominance of atmospheric motions over wakes in strongly unstable flows. Good agreement resulted with the use of an empirical model for wake-added turbulence to predict the variation of turbine power coherence with ambient turbulence intensity (R2 = 0.82), though other empirical relations may be applicable. It was shown that improperly accounting for turbine-turbine correlations can substantially impact power variance estimates on the order of a factor of 4.

Original languageEnglish (US)
Article number1486
JournalEnergies
Volume12
Issue number8
DOIs
StatePublished - Apr 19 2019

Fingerprint

Turbine
Farms
Turbines
Wake
Output
Turbulence
Temporal Correlation
Motion
Empirical Model
Wind Turbine
Large Eddy Simulation
Statistical Significance
Large eddy simulation
Wind turbines
Layout
Simulation
Unstable
Distinct
Predict
Prediction

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

Cite this

Tobin, Nicolas ; Lavely, Adam ; Schmitz, Sven ; Chamorro, Leonardo P. / Spatiotemporal correlations in the power output of wind farms : On the impact of atmospheric stability. In: Energies. 2019 ; Vol. 12, No. 8.
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abstract = "The dependence of temporal correlations in the power output of wind-turbine pairs on atmospheric stability is explored using theoretical arguments and wind-farm large-eddy simulations. For this purpose, a range of five distinct stability regimes, ranging from weakly stable to moderately convective, were investigated with the same aligned wind-farm layout used among simulations. The coherence spectrum between turbine pairs in each simulation was compared to theoretical predictions. We found with high statistical significance (p < 0.01) that higher levels of atmospheric instability lead to higher coherence between turbines, with wake motions reducing correlations up to 40{\%}. This is attributed to higher dominance of atmospheric motions over wakes in strongly unstable flows. Good agreement resulted with the use of an empirical model for wake-added turbulence to predict the variation of turbine power coherence with ambient turbulence intensity (R2 = 0.82), though other empirical relations may be applicable. It was shown that improperly accounting for turbine-turbine correlations can substantially impact power variance estimates on the order of a factor of 4.",
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Spatiotemporal correlations in the power output of wind farms : On the impact of atmospheric stability. / Tobin, Nicolas; Lavely, Adam; Schmitz, Sven; Chamorro, Leonardo P.

In: Energies, Vol. 12, No. 8, 1486, 19.04.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Spatiotemporal correlations in the power output of wind farms

T2 - On the impact of atmospheric stability

AU - Tobin, Nicolas

AU - Lavely, Adam

AU - Schmitz, Sven

AU - Chamorro, Leonardo P.

PY - 2019/4/19

Y1 - 2019/4/19

N2 - The dependence of temporal correlations in the power output of wind-turbine pairs on atmospheric stability is explored using theoretical arguments and wind-farm large-eddy simulations. For this purpose, a range of five distinct stability regimes, ranging from weakly stable to moderately convective, were investigated with the same aligned wind-farm layout used among simulations. The coherence spectrum between turbine pairs in each simulation was compared to theoretical predictions. We found with high statistical significance (p < 0.01) that higher levels of atmospheric instability lead to higher coherence between turbines, with wake motions reducing correlations up to 40%. This is attributed to higher dominance of atmospheric motions over wakes in strongly unstable flows. Good agreement resulted with the use of an empirical model for wake-added turbulence to predict the variation of turbine power coherence with ambient turbulence intensity (R2 = 0.82), though other empirical relations may be applicable. It was shown that improperly accounting for turbine-turbine correlations can substantially impact power variance estimates on the order of a factor of 4.

AB - The dependence of temporal correlations in the power output of wind-turbine pairs on atmospheric stability is explored using theoretical arguments and wind-farm large-eddy simulations. For this purpose, a range of five distinct stability regimes, ranging from weakly stable to moderately convective, were investigated with the same aligned wind-farm layout used among simulations. The coherence spectrum between turbine pairs in each simulation was compared to theoretical predictions. We found with high statistical significance (p < 0.01) that higher levels of atmospheric instability lead to higher coherence between turbines, with wake motions reducing correlations up to 40%. This is attributed to higher dominance of atmospheric motions over wakes in strongly unstable flows. Good agreement resulted with the use of an empirical model for wake-added turbulence to predict the variation of turbine power coherence with ambient turbulence intensity (R2 = 0.82), though other empirical relations may be applicable. It was shown that improperly accounting for turbine-turbine correlations can substantially impact power variance estimates on the order of a factor of 4.

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