Voltage quality monitoring system for distribution networks based on the one map of power grid
基于电网一张图的配电网电压质量监测系统研究

摘要

配电网向新型电力系统转型加速，设备激增与传统管理模式适配性不足的矛盾凸显，拓扑数据以非结构化图模存储，关键业务数据依赖人工提取整理，更新滞后，电压监测需要定时查询，无法实时捕捉波动，追溯困难，形成多系统数据孤岛，跨平台查询效率低，制约运维效能。针对上述问题，本文以电网一张图为核心，构建数据接入、治理、建模、应用的全流程技术体系，优化电压质量监测系统。整合用电信息采集、配电自动化等多源数据，涵盖拓扑关联、电压时序、负荷及用户档案等信息，通过剔除异常值、补全缺失数据、统一编码格式完成标准化治理，贯通拓扑逻辑。构建融合异常检测算法与分类模型的电压研判模型，通过异常检测算法过滤偶发波动，结合用户特性差异化进行判定，实现电压质量全景监测、精准预警及主动检修，为配电网数字化转型提供技术支撑，助力精益化运维升级。

Abstract

The transformation of the distribution network to a new power system is accelerating. The contradiction between the surge in equipment and the insufficient adaptability of the traditional management mode has become prominent. Topological data is stored in an unstructured graph model, and key business data depends on manual extraction and organization, resulting in lagged updates. Voltage monitoring requires regular queries, making it impossible to capture fluctuations in real-time and difficult to trace. This has led to data silos in multiple systems, low cross-platform query efficiency, and restricted operation and maintenance efficiency. In response to the above problems, this research takes the One Map of the Power Grid as the core and constructs a full-process technical system of data access-governance-modeling-application, with a focus on breaking through the voltage quality monitoring module. It integrates multi-source data such as power consumption information collection and distribution automation, covering information such as topological associations, voltage time series, load, and user profiles. Standardized governance is completed by eliminating outliers, complementing missing data, and unifying the coding format to connect topological logic. A voltage judgment model integrating an anomaly detection algorithm and a classification model is constructed. The anomaly detection algorithm filters out occasional fluctuations, and combined with the differential determination of user characteristics, it realizes panoramic monitoring, accurate early warning, and proactive maintenance of voltage quality, providing technical support for the digital transformation of the distribution network and helping to upgrade the lean operation and maintenance.