A self-tuning NeuroFuzzy feedback linearization-based damping control strategyfor multiple HVDC links

Abstract

This research work proposes a multi-input multi-output (MIMO) online adaptive feedback linearizationNeuroFuzzy control (AFLNFC) scheme to improve the damping of low frequency oscillations (LFOs) in an AC/DCpower system. Optimized NeuroFuzzy identi cation architecture online captures the oscillatory dynamics of the powersystem through wide area measurement system (WAMS)-based measured speed signals of machines. Based on theidenti ed power system model, the appropriate control law is derived through feedback linearization control with a self-tuned coefficient vector. The generated control signal modulates the real power ow through a high voltage direct current(HVDC) link during perturbed operating conditions and enhances system stability. The effectiveness of the proposedcontrol strategy is demonstrated through different contingency conditions of a multi-machine test power system withmultiple HVDC links. The results validate the signi cance of the proposed control strategy to improve the capability ofHVDC links to damp inter-area modes of LFOs. The proposed MIMO AFLNFC performance is bench-marked againstconventional PID based supplementary control.