Design Neural Damper Vibration to the Improve the Stability of Electric Power Systems

The Research Of A New Methodology For The Vibration Damper Depends On His Work On Neural Networks, In Order To Reduce The Damping Of Electrical System And Find Out The Effectiveness Of Damper Proposed In The Stability Of The System, So By Comparing It With Traditionally Power System Stabilizer, It Depends On Neural Network Process The Signal Of Rotation Speed Of The Generator To Control Of The Irritation Synchronous Machine, The Designed Damper Showed Ability To Reduce Amplitude Vibrations Arising From Failures And Thus Reduce The Time Of Damping By Providing Additional Effort To Signal Entered To The Agitation System.
Characterized The Proposed Technical Possibility of Further Improving the Dynamic Stability and Thus the Stability of the Electrical System

本研究提出一种基于神经网络（Neural Networks）的振动阻尼器（Vibration Damper）新方法，旨在降低电气系统阻尼，并验证所提阻尼器在系统稳定性中的应用效果。为此，将其与传统电力系统稳定器（Power System Stabilizer）进行对比。该方法依托神经网络处理发电机转速信号，以控制励磁同步电机。所设计的阻尼器可有效降低故障引发的振动幅值，并通过为输入至励磁系统的信号提供额外辅助量，缩短阻尼响应时长。
该所提技术具备进一步提升电力系统动态稳定性，进而强化整体电气系统稳定性的技术潜力。