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.