Liu Yanchi, Wang Xue, Liu Youda, Cui Sujin
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2016 Jun 27;16(7):946. doi: 10.3390/s16070946.
Power quality analysis issues, especially the measurement of harmonic and interharmonic in cyber-physical energy systems, are addressed in this paper. As new situations are introduced to the power system, the impact of electric vehicles, distributed generation and renewable energy has introduced extra demands to distributed sensors, waveform-level information and power quality data analytics. Harmonics and interharmonics, as the most significant disturbances, require carefully designed detection methods for an accurate measurement of electric loads whose information is crucial to subsequent analyzing and control. This paper gives a detailed description of the power quality analysis framework in networked environment and presents a fast and resolution-enhanced method for harmonic and interharmonic measurement. The proposed method first extracts harmonic and interharmonic components efficiently using the single-channel version of Robust Independent Component Analysis (RobustICA), then estimates the high-resolution frequency from three discrete Fourier transform (DFT) samples with little additional computation, and finally computes the amplitudes and phases with the adaptive linear neuron network. The experiments show that the proposed method is time-efficient and leads to a better accuracy of the simulated and experimental signals in the presence of noise and fundamental frequency deviation, thus providing a deeper insight into the (inter)harmonic sources or even the whole system.
本文探讨了电能质量分析问题,特别是信息物理能源系统中谐波和间谐波的测量。随着电力系统出现新情况,电动汽车、分布式发电和可再生能源的影响对分布式传感器、波形级信息和电能质量数据分析提出了额外要求。谐波和间谐波作为最显著的干扰,需要精心设计检测方法,以准确测量电负载,其信息对于后续分析和控制至关重要。本文详细描述了网络环境下的电能质量分析框架,并提出了一种用于谐波和间谐波测量的快速且分辨率增强的方法。所提出的方法首先使用单通道版本的稳健独立分量分析(RobustICA)有效地提取谐波和间谐波分量,然后通过三个离散傅里叶变换(DFT)样本以很少的额外计算估计高分辨率频率,最后使用自适应线性神经网络计算幅度和相位。实验表明,所提出的方法具有时间效率,并且在存在噪声和基频偏差的情况下,能够使模拟信号和实验信号具有更高的精度,从而为(间)谐波源甚至整个系统提供更深入的见解。