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本研究提出一种面向振动阻尼器（Vibration Damper）的全新方法论，其研发依托神经网络（Neural Networks）技术开展。本研究旨在降低电力系统阻尼，并通过与传统电力系统稳定器（Power System Stabilizer）对比，验证所提阻尼器在系统稳定性中的应用有效性。该方法借助神经网络处理发电机转速信号，以实现对同步电机励磁的控制。所设计的阻尼器能够削弱故障引发的振动幅值，并通过为励磁系统输入信号提供额外辅助分量，缩短阻尼响应时间。 所提出的技术具备进一步提升电力系统动态稳定性，进而提升系统整体稳定性的潜力。