Adaptive feedback linearization based HVDC damping control paradigm for power system stability enhancement

Saghir Ahmad, L. Khan
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引用次数: 3

Abstract

This research work proposes an application of conjugate gradient algorithm for optimization of adaptive Feedback Linearization Control (FBLC) strategy for damping power system oscillations through HVDC link. The nonlinear supplementary control scheme is based on real-time optimized NeuroFuzzy identification of the power system dynamics. A self-tuned (FBLC) is employed to derive appropriate control law to modulate the real power flow through HVDC system and improve its damping. Validation of the performance of control scheme is carried out through different fault situations of two-area test power system and bench-marked against the gradient descent based FBLC. The results obtained from the proposed control strategy exhibit significant stability improvement of the power system in transient-state and steady-state conditions.
基于自适应反馈线性化的高压直流阻尼控制模式增强电力系统稳定性
本研究提出应用共轭梯度算法优化自适应反馈线性化控制(FBLC)策略,通过高压直流链路抑制电力系统振荡。非线性补充控制方案是基于实时优化的电力系统动态神经模糊辨识。采用自调谐(FBLC)方法推导出合适的控制律,对直流系统的实际潮流进行调制,提高系统的阻尼。通过两区试验电力系统的不同故障情况对控制方案的性能进行了验证,并对基于梯度下降的FBLC进行了基准测试。结果表明,该控制策略在暂态和稳态条件下均显著提高了电力系统的稳定性。
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