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首页> 外文期刊>IEEE Transactions on Power Delivery >Modeling and Forecasting Nonstationary Voltage Fluctuation Based on Grey System Theory
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Modeling and Forecasting Nonstationary Voltage Fluctuation Based on Grey System Theory

机译:基于灰色系统理论的非平稳电压波动建模与预测

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摘要

Conventional voltage fluctuation, which causes light to flicker, is modeled by some sinusoidal signals which are modulated in voltage amplitude. In this approximate model, amplitude fluctuation is assumed to be stationary and deterministic. Field measurements and practical records show nonstationary treatments of the voltage fluctuation. Accurate modeling and forecasting of the envelope signal is necessary for power-quality enhancement and compensative devices control. In this paper, after extracting a voltage envelope by enhanced phase-locked loop, the envelope signal is filtered and uniformly sampled. Hence, the discrete-time envelope signal can be considered as a time series. Grey system theory-based models, such as GM(1,1) and the rolling Grey model are utilized to model and predict the time series. To increase the accuracy of resulting models, residuals are employed for the correction process. For this purpose, the Fourier correction Grey Model (FGM) is used to improve precision of GM(1,1). Since the number of used data in a Grey model is rather small, an iterative strategy is proposed to model and predict the entire envelope signal. In other words, the Grey models, which are local predictors, are modified to apply them as global ones by the proposed iterative method. The simulation results show that modified Grey models have high performances both on model fitting and forecasting. Among these Grey models, the precision of FGM is the highest. Also, the effect of datum numbers on the accuracy of models is investigated. The results confirm that the smaller number of data, the higher precision is yielded.
机译:引起光闪烁的常规电压波动是通过一些正弦信号建模的,这些信号的电压幅度已调制。在这个近似模型中,振幅波动被假定为固定的和确定的。现场测量和实际记录显示了电压波动的非平稳处理。包络信号的准确建模和预测对于提高功率质量和补偿设备控制是必需的。本文通过增强锁相环提取电压包络后,对包络信号进行滤波和均匀采样。因此,离散时间包络信号可以被认为是时间序列。基于灰色系统理论的模型,例如GM(1,1)和滚动灰色模型,用于建模和预测时间序列。为了提高所得模型的准确性,将残差用于校正过程。为此,傅立叶校正灰色模型(FGM)用于提高GM(1,1)的精度。由于格雷模型中使用的数据数量很少,因此提出了一种迭代策略来对整个包络信号进行建模和预测。换句话说,通过所提出的迭代方法,对作为局部预测变量的格雷模型进行了修改,以将其作为全局变量进行应用。仿真结果表明,改进的灰色模型在模型拟合和预测方面均具有较高的性能。在这些Gray模型中,FGM的精度最高。此外,还研究了基准数对模型精度的影响。结果证实,数据量越少,产生的精度越高。

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