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Improvement of AEP Predictions with Time for Swedish Wind Farms

Author

Listed:
  • Erik Möllerström

    (School of Business, Innovation and Sustainability, Halmstad University, P.O. Box 823, SE-301 18 Halmstad, Sweden)

  • Sean Gregory

    (School of Business, Innovation and Sustainability, Halmstad University, P.O. Box 823, SE-301 18 Halmstad, Sweden)

  • Aromal Sugathan

    (School of Business, Innovation and Sustainability, Halmstad University, P.O. Box 823, SE-301 18 Halmstad, Sweden)

Abstract

Based on data from 2083 wind turbines installed in Sweden from 1988 onwards, the accuracy of the predictions of the annual energy production (AEP) from the project planning phases has been compared to the actual wind-index-corrected production. Both the electricity production and the predicted AEP come from Vindstat, a database that collects information directly from wind turbine owners. The mean error for all analyzed wind turbines was 13.0%, which means that, overall, the predicted AEP has been overestimated. There has been an improvement of accuracy with time with an overestimation of 8.2% for wind turbines installed in the 2010s, however, the continuous improvement seems to have stagnated around 2005 despite better data availability and continuous refinement of methods. Dividing the results by terrain, the error is larger for wind turbines in open and flat terrain than in forest areas, indicating that the reason behind the error is not the higher complexity of the forest terrain. Also, there is no apparent increase of error with wind farm size which could have been expected if wind farm blockage effect was a main reason for the overestimations. Besides inaccurate AEP predictions, a higher-than-expected performance decline due to inadequate maintenance of the wind turbines may be a reason behind the AEP overestimations. The main sources of error are insecurity regarding the source of AEP predictions and the omission of mid-life alterations of rated power.

Suggested Citation

  • Erik Möllerström & Sean Gregory & Aromal Sugathan, 2021. "Improvement of AEP Predictions with Time for Swedish Wind Farms," Energies, MDPI, vol. 14(12), pages 1-12, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3475-:d:573602
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    References listed on IDEAS

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