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A case study of space-time performance comparison of wind turbines on a wind farm

Author

Listed:
  • Ding, Yu
  • Kumar, Nitesh
  • Prakash, Abhinav
  • Kio, Adaiyibo E.
  • Liu, Xin
  • Liu, Lei
  • Li, Qingchang

Abstract

This paper presents an academia-industry joint case study, which was conducted to quantify and compare multi-year changes in power production performance of multiple turbines scattered over a mid-size wind farm. This analysis is referred to as a space-time performance comparison. One key aspect in power performance analysis is to have the wind and environmental inputs controlled for. This research employs, in a sequential fashion, two principal modeling components to exercise tight control of multiple input conditions—a covariate matching method, followed by a Gaussian process model-based functional comparison. The analysis method is applied to a wind farm that houses 66 turbines on a moderately complex terrain. The power production and environmental data span nearly four years, during which period the turbines have gone through multiple technical upgrades. The space-time analysis presents a quantitative and global picture showing how turbines differ relative to each other as well as how each of them changes over time.

Suggested Citation

  • Ding, Yu & Kumar, Nitesh & Prakash, Abhinav & Kio, Adaiyibo E. & Liu, Xin & Liu, Lei & Li, Qingchang, 2021. "A case study of space-time performance comparison of wind turbines on a wind farm," Renewable Energy, Elsevier, vol. 171(C), pages 735-746.
    • Handle: RePEc:eee:renene:v:171:y:2021:i:c:p:735-746
    DOI: 10.1016/j.renene.2021.02.136
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    References listed on IDEAS

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    1. Niu, Briana & Hwangbo, Hoon & Zeng, Li & Ding, Yu, 2018. "Evaluation of alternative power production efficiency metrics for offshore wind turbines and farms," Renewable Energy, Elsevier, vol. 128(PA), pages 81-90.
    2. Hwangbo, Hoon & Ding, Yu & Eisele, Oliver & Weinzierl, Guido & Lang, Ulrich & Pechlivanoglou, Georgios, 2017. "Quantifying the effect of vortex generator installation on wind power production: An academia-industry case study," Renewable Energy, Elsevier, vol. 113(C), pages 1589-1597.
    3. Kjellin, J. & Bülow, F. & Eriksson, S. & Deglaire, P. & Leijon, M. & Bernhoff, H., 2011. "Power coefficient measurement on a 12 kW straight bladed vertical axis wind turbine," Renewable Energy, Elsevier, vol. 36(11), pages 3050-3053.
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    Cited by:

    1. Pengfei Zhang & Zuoxia Xing & Shanshan Guo & Mingyang Chen & Qingqi Zhao, 2022. "A New Wind Turbine Power Performance Assessment Approach: SCADA to Power Model Based with Regression-Kriging," Energies, MDPI, vol. 15(13), pages 1-15, July.
    2. Davide Astolfi & Ravi Pandit & Ludovico Terzi & Andrea Lombardi, 2022. "Discussion of Wind Turbine Performance Based on SCADA Data and Multiple Test Case Analysis," Energies, MDPI, vol. 15(15), pages 1-17, July.
    3. Davide Astolfi & Ravi Pandit & Andrea Lombardi & Ludovico Terzi, 2022. "Multivariate Data-Driven Models for Wind Turbine Power Curves including Sub-Component Temperatures," Energies, MDPI, vol. 16(1), pages 1-18, December.
    4. Francesco Castellani & Ravi Pandit & Francesco Natili & Francesca Belcastro & Davide Astolfi, 2023. "Advanced Methods for Wind Turbine Performance Analysis Based on SCADA Data and CFD Simulations," Energies, MDPI, vol. 16(3), pages 1-15, January.

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