基于频率测量的电力系统惯性估计

J. Hartono, P. Pramana, A. A. Kusuma, B. S. Munir
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引用次数: 1

摘要

如果系统中存在任何功率偏差,则系统惯性的大小决定了频率的变化率。因此,为了在系统中断时获得准确的防御方案,必须进行惯性量的估计。此外,还可以利用惯性大小来确定功率偏差的大小,使防御方案能够更准确地进行减载。因此,本研究将讨论仅使用频率测量数据使用人工神经网络(ANN)估计系统惯性的方法。从功率摆方程的仿真结果中获得了人工神经网络的训练和验证数据。然后,利用人工神经网络从实际测量数据中估计孤立系统的惯性量。结果表明,仅用频率测量数据估计系统惯量和功率偏差的幅度与实际测量结果接近。此外,这种了解系统惯性的方法将在公司中使用,以确定针对不同系统惯性的适当防御方案。
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Power System Inertia Estimation Based on Frequency Measurement
The magnitude of system inertia determines the rate of frequency change if there is any power deviation in the system. Thus, estimation of inertia magnitude is essential to be performed in order to obtain accurate defense scheme when the system is interrupted. In addition, the inertia magnitude can also be used to determine the magnitude of power deviation, so that defense scheme can perform load shedding more accurately. Therefore, this study will discuss about the method for estimating system inertia using Artificial Neural Network (ANN) only with frequency measurement data. The training and validation data for ANN are obtained from the simulation results of power swing equation. After that, the ANN network is used to estimate the inertia magnitude of isolated system from the real measurement data. The results show that the estimation of system inertia and power deviation only with frequency measurement data will have magnitude that close to the real measurement results. Furthermore, this method for knowing the system inertia will be used in the company to determine the proper defense scheme for different system inertia.
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