Load Profile Identification using Independent Component Analysis

E. Bobric, D. Irimia
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引用次数: 1

Abstract

The paper aims to establish the load profiles for the consumers, in a looped network, when the power circuits are known on the branches The algorithm used is independent component analysis (ICA), a statistic computational method that allows the extraction of additive components from a mixed signal. The method requires as restriction the statistically independence of the additive components. In the paper, ICA was used to reconstruct some statistically independent signals (power requests according to consumer load profiles) from a mixture of signals (power flows on branches). The ICA algorithm does not require knowledge of network parameters or configuration. The consumer load profiles obtained by the independent component method overlapped with a very good approximation over the real load graphs of consumers used in modeling.
基于独立分量分析的负荷轮廓识别
本文的目的是建立一个环路网络中,当分支上的功率电路已知时,用户的负荷分布,使用的算法是独立分量分析(ICA),这是一种统计计算方法,可以从混合信号中提取附加分量。该方法要求附加成分的统计独立性作为限制。本文使用ICA从混合信号(支路上的潮流)中重建一些统计上独立的信号(根据用户负载分布的电力请求)。ICA算法不需要了解网络参数或配置。独立分量法得到的用户负荷曲线与建模中使用的用户实际负荷曲线有很好的近似重叠。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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