Traditional analytical methods for determining the T-type equivalent circuit parameters of high-inertia energy storage synchronous condensers suffer from computational inaccuracies and time-varying magnetic saturation effects. To address these issues

this study proposes an innovative hybrid parameter identification model that combines an online parameter identification method with offline experimental testing. The online model

based on the mathematical representation of the doubly-fed induction machine in a two-phase synchronous rotating coordinate system

dynamically identifies stator inductance

excitation inductance

and rotor inductance in real-time using operational electrical quantities. The offline model employs no-load and grid-connected active power adjustment tests to achieve precise parameter measurements. A high-inertia energy storage condenser grid transient simulation model was developed

integrating the online parameter identification algorithm to update controller parameters in real-time. Experimental validation was conducted using an existing doubly-fed prototype of equivalent capacity. Both simulation and experimental results demonstrate that the proposed T-type equivalent circuit parameter identification model exhibits rapid convergence

high accuracy

strong adaptability to operational conditions

and practical engineering applicability. The online identification model achieves an average convergence time of less than 0.85 seconds under charging/discharging

steady-state reactive power support

and transient switching conditions. Steady-state identification errors are controlled within 1%

while transient errors remain below 30% of the offline test results. Real-time controller parameter updates based on online identification ensure precise tracking of active and reactive power targets. Additionally

when machine parameters vary dynamically

the online model optimizes controller parameters to enhance control performance. Offline experimental tests reveal that stator inductance

excitation inductance

and rotor inductance exhibit significant excitation current-dependent characteristics

displaying a nonlinear attenuation trend as excitation current increases

further validating the necessity of parameter identification. This research improves the modeling accuracy of high-inertia energy storage condensers and refines control system parameter tuning

thereby enhancing the vector control performance of doubly-fed induction machine and the precision of grid transient simulations. The findings provide theoretical support for the intelligent control of high-inertia energy storage synchronous condensers.