基于人工神经网络的电力系统稳定器

J. Kumar, P. P. Kumar, Aeidapu Mahesh, Ankit Shrivastava
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引用次数: 9

摘要

介绍了一种基于人工神经网络(ANN)的电力系统自整定自适应稳定器的系统设计方法。利用人工神经网络对PSS的参数进行自整定,实时稳定前置PSS的增益Kstab和时间常数T1。人工神经网络的输入为发电机终端有功功率(P)和无功功率(Q)。研究了基于人工神经网络的自调谐PSS (ST-ANNPSS)系统在各种负载条件下的动态性能。利用Matlab/Simulink的神经网络工具箱进行仿真。仿真和实验结果表明,该系统具有良好的动态性能。
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Power system stabilizer based on artificial neural network
This paper describes a systematic approach for designing a self-tuning adaptive power system stabilizer (PSS) based on artificial neural network (ANN). An ANN is used for self-tuning the parameters of PSS e.g. stabilizing gain Kstab and time constant (T1) for Lead PSS in realtime. The inputs to the ANN are generator terminal active power (P) and reactive power (Q). Investigations are carried out to assess the dynamic performance of the system with self-tuning PSS based on ANN (ST-ANNPSS) over a wide range of loading conditions. The simulations are performed using Matlab/Simulink's neural network toolbox. The simulation and experimental results demonstrate the effective dynamic performance of the proposed system.
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