TY - JOUR
T1 - Mesoscale model evaluation with coherent Doppler lidar for wind farm assessment
AU - Krishnamurthy, Raghavendra
AU - Calhoun, Ronald
AU - Billings, Brian
AU - Doyle, James D.
N1 - Funding Information:
hospitality of the Mesoscale Modeling Section of the Naval Research Laboratory in Monterey, California, was much appreciated and allowed the participation of R. Calhoun through the ONR Fellow Program during summer of 2011. The fourth author (JDD) acknowledges the support from the Naval Research Laboratory base programme. Finally, the authors thank the reviewers for their constructive comments, which improved the quality of this letter.
PY - 2013
Y1 - 2013
N2 - Wind measurements are fundamental inputs for wind resource assessment and the performance of wind farms. Common approaches for wind energy yield assessment are based on (1) observational data from surface station networks and (2) high-resolution computational fluid dynamic or mesoscale models. In this letter, we investigate the potential of applying a high-resolution nested mesoscale model, Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), to predict low-level wind characteristics for wind farm domains. The model results are compared to scanning coherent Doppler lidar and tower measurements for a wind energy development. This letter focuses on the magnitude of difference between observations and simulations used for wind energy assessment. The results highlight the challenge for straight-forward application of mesoscale models, even well-established models with a relatively fine resolution on the inner nest (333 m), to produce wind predictions of sufficient fidelity and accuracy appropriate for resource assessment or operational support for individual wind farms.While many of the average wind flow features are captured by the model, their detailed spatial and temporal evolution may be improved through tighter integration with local sensor data.
AB - Wind measurements are fundamental inputs for wind resource assessment and the performance of wind farms. Common approaches for wind energy yield assessment are based on (1) observational data from surface station networks and (2) high-resolution computational fluid dynamic or mesoscale models. In this letter, we investigate the potential of applying a high-resolution nested mesoscale model, Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS), to predict low-level wind characteristics for wind farm domains. The model results are compared to scanning coherent Doppler lidar and tower measurements for a wind energy development. This letter focuses on the magnitude of difference between observations and simulations used for wind energy assessment. The results highlight the challenge for straight-forward application of mesoscale models, even well-established models with a relatively fine resolution on the inner nest (333 m), to produce wind predictions of sufficient fidelity and accuracy appropriate for resource assessment or operational support for individual wind farms.While many of the average wind flow features are captured by the model, their detailed spatial and temporal evolution may be improved through tighter integration with local sensor data.
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U2 - 10.1080/2150704X.2013.769285
DO - 10.1080/2150704X.2013.769285
M3 - Article
AN - SCOPUS:85008798876
SN - 2150-704X
VL - 4
SP - 579
EP - 588
JO - Remote Sensing Letters
JF - Remote Sensing Letters
IS - 6
ER -