Model Order Reduction of Wind Farms: Linear Approach

Abstract

This paper presents three types of linear model order reduction (MOR) technique, namely singular value decomposition (SVD) based, Krylov-based, and modal truncation based 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 practical-sized 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 terms of frequency domain indices and waveform agreement at the point of common coupling (PCC).