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

Authors

SAGHIR AHMAD
LAIQ KHAN

DOI

10.3906/elk-1506-38

Abstract

This research work proposes a multi-input multi-output (MIMO) online adaptive feedback linearization NeuroFuzzy control (AFLNFC) scheme to improve the damping of low frequency oscillations (LFOs) in an AC/DC power system. Optimized NeuroFuzzy identification architecture online captures the oscillatory dynamics of the power system through wide area measurement system (WAMS)-based measured speed signals of machines. Based on the identified 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 flow through a high voltage direct current (HVDC) link during perturbed operating conditions and enhances system stability. The effectiveness of the proposed control strategy is demonstrated through different contingency conditions of a multi-machine test power system with multiple HVDC links. The results validate the significance of the proposed control strategy to improve the capability of HVDC links to damp inter-area modes of LFOs. The proposed MIMO AFLNFC performance is bench-marked against conventional PID based supplementary control.

Keywords

Inter-area oscillation, high voltage direct transmission, adaptive NeuroFuzzy system, feedback linearization, nonlinear control

First Page

913

Last Page

938

Recommended Citation

AHMAD, SAGHIR and KHAN, LAIQ (2017) "A self-tuning NeuroFuzzy feedback linearization-based damping control strategy for multiple HVDC links," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 25: No. 2, Article 21. https://doi.org/10.3906/elk-1506-38
Available at: https://journals.tubitak.gov.tr/elektrik/vol25/iss2/21