Stability Enhancement of a PMSG-Based Offshore Wind Farm Fed to a Multi-Machine System Through an LCC-HVDC Link

Adaptive-network-based fuzzy inference system (ANFIS) is an adaptation and robustness method since it combines the advantages of artificial neural network (ANN) and fuzzy logic controller (FLC). Besides, ANFIS is also a nonlinear controller that can be used to improve stability of the studied system under different operating points. This paper presents the stability-improvement results of an offshore wind farm (OWF) fed to a multi-machine system through a high-voltage direct-current (HVDC) link based on line-commutated converter (LCC). An effective control scheme using a designed ANFIS damping controller at the inverter station of the HVDC link to achieve damping improvement of the studied system is proposed. A frequency-domain scheme based on eigenvalue and root-loci technique is carried out to compare the effectiveness of the proposed ANFIS control scheme and a modal-control designed PID damping controller. A time-domain scheme based on a nonlinear system model subject to a three-phase short-circuit fault is also utilized to examine the effectiveness of the proposed control scheme. Comparative simulation results show that the two damping controllers can contribute adequate damping characteristics to the dominant modes of the studied system while the designed ANFIS damping controller is shown to be superior for improving the stability of the studied system subject to a severe disturbance.