电网中电压波动源选择性识别与定位过程中的分解问题
Decomposition Problem in Process of Selective Identification and Localization of Voltage Fluctuations Sources in Power Grids
AI总结：
本文研究了电网中电压波动源选择性识别与定位的分解问题，采用增强经验小波变换（EEWT）算法进行分解，并基于实际电网数据揭示了该方法导致的定位错误及其潜在原因。
摘要：
电压波动是电网中常见的扰动，因此，有效且选择性地识别和定位各个电压波动源的过程对于最小化此类扰动是必要的。识别和定位扰动负荷过程中的选择性可以通过使用级联模块来实现：解调、分解和传播评估。这种方法的有效性与所使用的分解方法密切相关。本文针对所选的电压波动源选择性识别与定位方法，提出了其分解过程的问题，其中将增强经验小波变换（EEWT）算法用作分解方法。本文展示了来自实际电网的部分研究结果，对于该电网，所选方法的结果在电压波动源的识别和定位过程中导致了错误。基于所获得的研究结果，讨论了与分解过程相关的此类错误的潜在原因。
英文摘要：
Voltage fluctuations are common disturbances in power grids, therefore the effective and selective process of identification and localization of individual voltage fluctuations sources is necessary for the minimization of such disturbances. Selectivity in the process of identification and localization disturbing loads is possible by the use cascade of blocks: demodulation, decomposition and propagation assessment. The effectiveness of this approach is closely related to the used method of decomposition. The paper presents the problem of decomposition process for the selected method of selective identification and localization of voltage fluctuation sources, in which the algorithm of enhanced empirical wavelet transform (EEWT) is used as the decomposition method. The paper presents selected research results from the real power grid, for which the result of selected approach causes mistakes in the process of identification and localization of voltage fluctuations sources. The potential causes of such mistakes related to the decomposition process are discussed on the basis of obtained research results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
