基于电压序列相似性的户变关系与相别识别
摘要：随着低压配电网的改造升级，台区户变关系变化频繁，为解决时有发生的用户台区挂错现象，提出一种利用改进的基于密度的点排序识别聚类结构（ordering points to identify the clustering structure, OPTICS）的台区户变关系识别和相别识别方法。首先，对配网电压序列的相关性进行定性分析，提出利用电压时序序列作为分析识别的数据基础；其次，采用改进的自适应分段聚合近似（adaptive piecewise aggregate approximation, APAA）对电压序列进行降维处理，提取能够反映电压特征的低维向量；然后利用改进的OPTICS算法对所提取的特征向量进行聚类分析，识别台区的户变关系和相别关系；最后，基于实际的台区数据进行算例分析，验证了所提方法的准确性。
Abstract:With the renovation and upgrading of the low-voltage distribution network, the transformer-customer relationship changes frequently. In order to solve the user's hanging wrong phenomenon that happens from time to time in the substation area, an identification method of the transformer-customer relationship and the phase difference in the substation area was proposed by using an improved density-based point sorting recognition clustering structure (abbr. OPTICS). Firstly, the correlation of the distribution network voltage series was analyzed qualitatively, proposing the use of voltage time series as the data basis for analysis and recognition. Secondly, the improved adaptive piecewise aggregate approximation (abbr. APAA) was used to reduce the dimensionality of the voltage series, extracting the low-dimensional vectors that can reflect the voltage characteristics. Thirdly, the extracted feature vectors were clustered by using the improved OPTICS algorithm to identify the transformer-customer relationship and phase relationships of the substation area. Finally, an example analysis was carried out based on the actual data of the substation area, which verifies the accuracy of the proposed method.
标题：基于电压序列相似性的户变关系与相别识别
英文标题：Tansformer-customer Relationship and Phase Identification Based on Voltage Sequence Similarity
作者：楚成博, 朱丽萍, 方磊, 樊清川, 吴蓉, 袁捷,
关键词：户变关系, 相别识别, 时序序列数据, 特征提取, 自适应分段聚合近似, 基于密度的聚类算法,
发表日期：2024-12-10
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