This paper presents three types of linear model order reduction (MOR) technique, namely singular value decomposition (SVD)-based, Krylov-based, and modal truncationbased type applied to large-scale wind farm models. The first type includes a Balanced Truncation (BT) and Alternating Direction Implicit (ADI)-based BT method, while the second type encompasses a Rational Krylov (RK), and Iterative Rational Krylov Algorithm (IRKA) method. In the third type, a Subspace Accelerated MIMO Dominant Pole Algorithm (SAMDP) method is used. The effectiveness of these methods are tested on practicalsized wind farms with 90, 120 and 210 doubly-fed induction generators (DFIGs). Merits and demerits of each method are discussed in detail. The reduced order model (ROM) of wind farm is validated against the full order model (FOM) in term of frequency domain indices and waveform agreement at the point of common coupling (PCC).

This paper presents a method to develop computationally efficient dynamic model of a wind farm suitable for large disturbance simulation. The method based on a Trajectory Piecewise Linear (TPWL) approximation uses single and multiple training trajectory to develop a nonlinear reduced order model (ROM). Simulation results using a small demonstration wind farm system and a large practical wind farm system are discussed to demonstrate the effectiveness of the model in capturing dynamic behaviour of wind farm following large disturbances.

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This paper presents three types of linear model order reduction (MOR) technique, namely singular value decomposition (SVD)-based, Krylov-based, and modal truncationbased type applied to large-scale wind farm models. The first type includes a Balanced Truncation (BT) and Alternating Direction Implicit (ADI)-based BT method, while the second type encompasses a Rational Krylov (RK), and Iterative Rational Krylov Algorithm (IRKA) method. In the third type, a Subspace Accelerated MIMO Dominant Pole Algorithm (SAMDP) method is used. The effectiveness of these methods are tested on practicalsized wind farms with 90, 120 and 210 doubly-fed induction generators (DFIGs). Merits and demerits of each method are discussed in detail. The reduced order model (ROM) of wind farm is validated against the full order model (FOM) in term of frequency domain indices and waveform agreement at the point of common coupling (PCC).