LVDN中基于数据分析的相位识别算法可信度评估

Kun Li, Yongjun Zhang, Wenhui Hong, Thanh-tung Ha
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引用次数: 0

摘要

在低压配电网中,相位识别算法的识别精度很难确定。针对这一问题,本文提出了一种基于数据分析的低压配电网相识别算法可信度评估方法。本文从基于数据分析的相位识别算法的原理入手。然后考虑到智能电表测量数据质量的影响,提出了数据完成率、有效电表完成率、三相电压不平衡率、明显使用率和时间表比5个可信度评价指标。其次,建立了基于层次分析法和多项式拟合的相位识别结果可信度评价模型。最后,利用广东两个实际低压配电网的实际电表数据集进行了仿真,验证了本文方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Credibility Evaluation of the Phase Identification Algorithm Based on Data Analysis in LVDN
In the low-voltage distribution network, it’s hard to know the identification accuracy of the phase identification algorithm. To solve this problem, this paper proposes a credibility evaluation method which can assess the results of phase identification algorithm, based on data analysis, in the low-voltage distribution network. In this paper, we start from the mechanism of the phase identification algorithm based on the data analysis. Then considering the effect of data quality measured by smart meters, we propose five evaluation indicators of credibility including completion of data, completion of valid meters, unbalance of three-phase voltage, obvious users rate and ratio of time to meters. Next, we build the credibility evaluation model of phase identification result based analytic hierarchy process and polynomial fitting. Finally, simulation results using the real meter datasets of two real low-voltage distribution networks in Guangdong, China to demonstrate the performance of our method.
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