Intelligent Feedback Linearization based adaptive control paradigm for damping power system oscillations

Saghir Ahmad, L. Khan
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Abstract

This research work proposes an adaptive feedback linearization control strategy for nonlinear identification and control of power system oscillations through HVDC link. The supplementary control scheme is based on real-time optimized NeuroFuzzy identification of power system dynamics. A self-tuned Feedback Linearization Control (FBLC) is employed to derive appropriate control law to modulate the real power flow through HVDC link and improve the damping assistance provided by HVDC system during perturbed operating conditions. Validation of the performance of control scheme is carried out through different contingency conditions of two-area test power system. The performance of the proposed control system is bench-marked against the conventional control scheme. The simulation results obtained from the proposed control strategy exhibit significant stability improvement of power system in transient and steady-state conditions.
基于智能反馈线性化的自适应控制模式阻尼电力系统振荡
本文提出了一种自适应反馈线性化控制策略,用于高压直流链路的电力系统振荡非线性辨识与控制。补充控制方案基于实时优化的电力系统动态神经模糊辨识。采用自调谐反馈线性化控制(FBLC),推导出合适的控制律,对直流电网实际潮流进行调制,提高直流系统在扰动工况下的阻尼辅助能力。通过两区试验电力系统的不同应急工况,对控制方案的性能进行了验证。该控制系统的性能与传统控制方案进行了基准测试。仿真结果表明,该控制策略在暂态和稳态条件下均能显著提高电力系统的稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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