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Table 3 Comparison of SSI analysis methods

From: Review of sub-synchronous interaction in wind integrated power systems: classification, challenges, and mitigation techniques

Analysis Techniques

Advantage

Limitations

Applications

Frequency scanning techniques

Simple and easy to implement by utilizing equivalent circuits or simulation tools

Computational attractive

Cost-effective

Approximate method

For accuracy, the results must be verified using time domain simulation

It is not possible to consider the dynamic properties of systems during faults

To identify steady-state SSR, SSTCI and SSCCI

To determine the system operating circumstances that influence SSI

Eigenvalue analysis

Accurate analysis and provides a clear insight into Subsynchronous interactions

Reveals details about the damping and frequency of every system mode

Finding the involvement of state variables and component sensitivity is simple

Restricted to very large systems

Nonlinearities cannot be included

Device switching characteristics are ignored

Expensive method

Require detailed system representation

Fails to identify transient SSR

Helpful for creating SSI countermeasure controllers

To determine the system's operational circumstances that affect SSI

Complex torque coefficients

Displaying the mechanical and electrical damping coefficient trends over a wide range of frequencies

Mostly applied to the mechanical oscillation

To identify SSTCI and torsional interaction of SSR

Impedance-based model analysis

Finding the oscillation path and component sensitivity is possible due to the impedance-network model, which preserves the network topology

Improved modeling methods and suitable stability criteria are required

Challenging frequency domain modeling techniques

Used for SSCCI analysis

Transient simulation analysis techniques

Allows for precise SSI investigations under varied disturbances

For self-excitation study, not recommended

Needs a thorough system representation

Not helpful for determining the internal relationships among different variables

Verify the outcomes of the eigenvalue and frequency scanning techniques