The Influence of Higher-order Disturbance Estimation on Wind Power Generation of WECS using SMC with Sensorless Wind Speed Estimation

Research output: Contribution to journalArticlepeer-review

Abstract

The increasing demand for environmentally friendly, renewable, and clean energy sources as a substitute to fossil fuels, which emit greenhouse gases, continues to rise. Nonetheless, extracting the maximum wind power through the wind energy conversion system (WECS) hinges on accurately measuring the generator's reference speed and the aerodynamic torque. This paper introduces an approach using an exponential disturbance estimator to extract the WECS's maximum power by estimating aerodynamic torque (Ta) and wind speed (v). Unlike most existing literature that assumes the behavior of the torque to change slowly, this paper offers a thorough investigation of the impact of fast-varying Ta on WECS's power harnessing using observer-based super-twisting sliding mode control (STSMC). Simulation results of reduced-intensity, fast-varying, and extremely fast-varying wind speeds for the zero-order (ZO), first-order (FO), and second-order (SO) Ta estimations were investigated. Though the incorporation of higher-order estimations improved the speed tracking performance and increased the maximum power extraction by about 6.5% for extremely varying wind profiles (from 182.15 kW to 193.92 kW), the ZO estimation almost extracted the same amount of power for fast-changing wind speed (151.87 kW vs 152.08 kW), and low-intensity wind force (6.86 kW vs 6.89 kW). Ultimately, the analyses suggested that in scenarios where the wind speed is not extremely changing, the ZO estimation proves effective, as the higher-order estimations will increase noise and the computational burden on the WECS.

Original languageEnglish
JournalIEEE Access
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • Disturbance observer
  • renewable energy sources
  • sensorless wind speed estimation
  • wind energy conversion system (WECS)

ASJC Scopus subject areas

  • General Computer Science
  • General Materials Science
  • General Engineering

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