Site Adaptation of the Reanalysis Data ERA5 on the Power Prediction of Wind Farms

Jin-Young Kim; Su-Jin Hwang; Hyun-Goo Kim; Chae-Young Park; Jun-Young Jeong

doi:10.7836/kses.2022.42.4.079

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2022 Vol.42, Issue 4 Preview Page Next Page

Research Article

Site Adaptation of the Reanalysis Data ERA5 on the Power Prediction of Wind Farms 풍력단지 발전량 예측에 대한 재해석 자료 ERA5의 현장적응

30 August 2022. pp. 79-91

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Abstract

Owing to the continuously improving spatial resolution and accuracy of the reanalysis data, a site adaptation case study was performed for the prediction of wind farm power output using ERA5, the 5th generation reanalysis data. The wind speed of the reanalysis data was substituted into the performance curve of the wind turbine by altitude and topographical speed up/down correction using the power law for maximizing the correlation between the predicted and actual power record. Cluster analysis was conducted to classify the wind farms into five groups, and representative onshore, inland, mountain wind farms were selected for case analysis from each cluster. Via the site adaptation of 41 wind farms in South Korea, the hourly, daily cumulative, and monthly cumulative correlation coefficients of the power output were calculated, which were 0.68, 0.79, and 0.85, respectively. In future, machine learning will be introduced for site adaptation in conjunction with the downscaling of wind resource maps by numerical weather prediction or computational fluid dynamics.

Keywords

Wind farm

Wind turbine

Power curve

Site adaptation

Reanalysis data

Cluster analysis

키워드

풍력단지

풍력터빈

성능곡선

현장적응

재해석 자료

군집분석

References

Fernández-Peruchena, C. M., Polo, J., Martín, L., and Mazorra, L., Site-adaptation of Modeled Solar Radiation Data: The SiteAdapt Procedure, Remote Sensing, Vol. 12, pp. 2127, 2020, http://dx.doi.org/10.3390/rs12132127. 10.3390/rs12132127

Polo, J., Wilbert, S., Ruiz-Arias, J. A., Meyer, R., Gueymard, C., Suri, M., Martin, L., Mieslinger, T., Blanc, P., Grant, I., Boland, J., Ineichen, P., Remund, J., Escobar, R., Troccoli, A., Sengupta, M., Nielsen, K. P., Renne, D., Geuder, N., and Cebecauer, T., Preliminary Survey on Site-adaptation Techniques for Satellite-derived and Reanalysis Solar Radiation Datasets, Solar Energy, Vol. 132, pp. 25-37, 2016, http://dx.doi.org/10.1016/j.solener.2016.03.001. 10.1016/j.solener.2016.03.001

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, T., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, O., Vamborg, F., Villaume, S., and Thépaut, J. N., The ERA5 Global Reanalysis, Quarterly J. of the Royal Meteorological Society, Vol. 146, pp. 1999-2049, 2020, https://doi.org/10.1002/qj.3803. 10.1002/qj.3803

Jourdier, B., Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to Simulate Wind Power Production over France, Advances in Science & Research, Vol. 17, pp. 63-77, 2020, https://doi.org/10.5194/asr-17-63-2020. 10.5194/asr-17-63-2020

Gualtieri, G., Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison Against Tall Towers, Energies, Vol. 14, pp. 4169, 2021, https://doi.org/10.3390/en14144169. 10.3390/en14144169

Kim, H. G., Kim, B. Y., Kang, Y. H., and Ha, Y. C., Estimation of Reference Wind Speeds in Offshore of the Korean Peninsula using Reanalysis Data Sets, New & Renewable Energy, Vol. 17, No. 4, pp. 9-16, 2021, http://dx.doi.org/10.7849/ksnre.2021.0022. 10.7849/ksnre.2021.0022

Bengtsson, L., Kanamitsu, M., Kållberg, P. W., and Uppala, S. M., FGGE 4-dimensional Data Assimilation at ECMWF, Bulletin of the American Meteorological Society, Vol. 63, pp. 29-43, 1982. 10.1175/1520-0477-63.3.277

Gibson, J. K., Kållberg, P., Uppala, S. M., Hernandez, A., Nomura, A., and Serrano, E., ECMWF Reanalysis Project Report 1, ERA-15 Description (Version 2), Technical Report, ECMWF, Reading, UK, 1999.

Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., da Costa Bechtold, V., Fiorino, M., Gibson, J. K., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Andersson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E. V., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., McNally, A. P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenberth, K. E.,Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J., The ERA-40 Reanalysis, Quarterly J. of the Royal Meteorological Society, Vol. 131, pp. 2961-3012, 2005, http://dx.doi.org/10.1256/qj.04.176. 10.1256/qj.04.176

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F., The ERA-Interim Reanalysis: Configuration and Performance of the Data Assimilation System, Quarterly J. of the Royal Meteorological Society, Vol. 137, pp. 553-597, 2011, https://doi.org/10.1002/qj.828. 10.1002/qj.828

Byun, J. K. and Koh, K. N., Application of ERA-Interim Reanalysis Data for Onshore and Offshore Wind Resource Assessment, J. of the Korean Solar Energy Society, Vol. 37, No. 2, pp. 1-11, 2017, https://doi.org/10.7836/kses.2017.37.2.001. 10.7836/kses.2017.37.2.001

Kim, H. G., Kim, J. S., Kang, Y. H., and Park, H. D., Classification of Wind Sector in Pohang Region using Similarity of Time-series Wind Vectors, J. of the Korean Solar Energy Society, Vol. 36, No. 1, pp. 11-18, 2016, https://doi.org/10.7836/kses.2016.36.1.011. 10.7836/kses.2016.36.1.011

Kim, J. Y., Kim, C. K., Hwang, S. J., and Kim, H. G., Cluster Analysis of Wind Zones using Various Similarity Measures, J. of the Wind Engineering Institute of Korea, Vol. 25, No. 3, pp. 111-117, 2021, https://doi.org/10.37109/weik.2021.25.3.111. 10.37109/weik.2021.25.3.111

Kim, H. G. and Kim, J. Y., Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement, Energies, Vol. 14, 2319, 2021, https://doi.org/10.3390/en14082319. 10.3390/en14082319

Woo, J. K., Kim, H. G., Kim, B. M., Paek, I. S., and Yoo, N. S., Prediction of Annual Energy Production of Gangwon Wind Farm using AWS Wind Data, J. of the Korean Solar Energy Society, Vol. 31, No. 2, pp. 72-81, 2011. 10.7836/kses.2011.31.2.072

Oh, M. C., Lee, J. H., Kim, J. Y., and Kim, H. G., Machine Learning-based Statistical Downscaling of Wind Resource Maps using Multi-resolution Topographical Data, Wind Energy, Vol. 25, No. 6, pp. 1121-1141, 2022, https://doi.org/10.1002/we.2718. 10.1002/we.2718

Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 42
No :4
Pages :79-91
Received Date : 2022-03-29
Revised Date : 2022-06-29
Accepted Date : 2022-07-24
DOI :https://doi.org/10.7836/kses.2022.42.4.079

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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