全面数据质量管理框架在配电网领域的应用分析

电力数据质量问题日益突出,影响了电力数据挖掘和能源大数据分析的准确性和有效性。本文针对当前电力系统新环境下配电网数据特点及产生数据质量问题的原因进行梳理,获得数据质量出现的主要影响因素;给出提升配电网数据质量的管理平台架构,并对数据质量评价和数据质量控制两个核心技术内容进行分析;提出考虑数据质量管理需求的异常数据剔除及修复策略,实现对不同类型的数据进行动态治理及数据修复。最后通过实际配电网数据验证了质量管理和提升效果。

Application Analysis of Comprehensive Data Quality Management Framework in Distribution Network

The problem of power data quality is becoming more and more serious,affecting the accuracy and effectiveness of power data mining and big data analysis of energy. In this paper,the characteristics of distribution network data under the new environment of power system at present and the causes of data quality problems are sorted out,thus obtaining the main influencing factors of data quality. The architecture of management platform for improving the data quality of distribution network is given,and the two core technologies(e.g.,data quality evaluation and data quality control)are analyzed. In addition,the strategy for eliminating and repairing the abnormal data with the consideration of data quality management requirements is proposed to realize the dynamic control and data repair for different types of data. Finally,the effects of quality management and improvement are verified based on some actual distribution network data.