High-accuracy  reconstruction  of  the  operational  state  is  essential  for  performance  evaluation  and  fault diagnosis of wind turbines. However, in practice, inaccurate wind speed measurements often lead to significant deviations in data analysis and state reconstruction, which directly compromise the accuracy and timeliness of wind turbine operation and maintenance.  To  address  this  issue,  this  study  starts  from  the  overall  mechanism  of  energy  capture  and  transfer  in  wind turbines, establishes a power flow model that integrates physics-based principles with data-driven approaches, and proposes a bisection-based method for estimating the rotor equivalent wind speed. The results demonstrate that the proposed method achieves high-consistency reproduction of key state variables—including rotor speed, output power, and pitch angle—under a wide range of operating conditions, including below rated wind speed, near rated wind speed, and in high wind speed regions. The consistency coefficient of field reproduced (CCFR) obtained by this method significantly outperforms that of conventional  methods  relying  on directly  measured  wind  speeds,  showing  excellent  engineering  applicability  and robustness.  The  proposed  wind  speed  estimation  method  enhances  the  accuracy  of  operating  condition  reproduction  and provides  a  reliable  data  foundation  and  technical  means  for  engineering  applications  such  as  performance  assessment, control parameter optimization, and fault early warning. It holds considerable value for practical field deployment.