A data mining method for obtaining global power quality index
A data mining method for obtaining global power quality index
复制标题
一种获取全局电能质量指数的数据挖掘方法
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
M. Moallem
中科院分区：
文献类型：
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作者：
S. Nourollah;M. Moallem
电力体制改革和电力市场竞争的新发展，使电能质量成为竞争的重要因素。然而，由于电能质量标准涉及的指标较多，寻找电能质量评价的方法非常困难。因此，基于标准测量获得单一的定量指标成为近年来研究的新挑战。由于从电能质量测量中获得了大量数据，因此需要数据挖掘方法。本文提出了一种数据挖掘方法来确定电能质量的全局指标。考虑了连续和离散的电能质量指标，基于合并和归一化的方法，针对每个电能质量指标提出了统一电能质量指标（UPQI）。指数标准化并分类。每个配电站点的电能质量水平由快速独立分量分析（Fast-ICA）算法确定。伊朗313个配电点的电能质量测量用于对配电系统中不同类型负载的指标进行分类。
The new development in power system such as restructuring and competetive electricity market make power quality an important factor in competition. However, to find a measure for power quality evaluation is very difficult due to many indices involved in power quality standards. For this reason, obtaining a single quantitative index based on the standard measurements has been a new challenge in recent researches. Data mining methods are required for this purpose due to the large amount of data obtained from power quality measurements. In this paper, a data mining method is proposed to determine a global index for power quality. The continuous and discrete indices of power quality are considered and the Unified Power Quality Index (UPQI) is presented for each power quality index, based on the method of incorporation and normalization. The indices normalized and classified. The power quality level of each distribution site is determined by the Fast Independent Component Analysis (Fast-ICA) algorithm. The power quality measurements of 313 distribution sites in Iran are used to classify the indices for different type of loads in the distribution system.