Accurate inverter impedance information is essential for analyzing and solving issues related to the stability and power quality of new energy grid integration. To address the high cost and safety risks of injected impedance measurement

where disturbances are intentionally injected into the system

as well as the low accuracy of non-injected impedance estimation

a coordinated injected and non-injected inverter impedance estimation method is proposed. First

an inverter parameter estimation model is constructed

using historical impedance measurement data as input and minimizing the deviation between the estimated and measured impedance values as the objective. Considering constraints from the filtering circuitry and control loops

optimal inverter parameters are obtained. Second

a dynamic impedance clustering method is proposed

which uses the solved inverter parameters as features to classify and aggregate impedance measurement data

while the clustering results characterize inverter operating sub-conditions. Then

an inverter impedance estimation method is proposed to construct the feature matrix of sub-conditions based on historical impedance measurements

and real-time power data acquired from non-injected measurements are matched with elements of the feature matrix to estimate inverter impedance in real time. Finally

simulation results verify that the proposed impedance estimation method has strong anti-interference ability

achieves higher accuracy than either injected-only or non-injected-only methods

imposes less impact on the system

and holds practical engineering value.