基于大数据的电网业务系统设备关联技术研究

Research on equipment association technology of power grid business system based on big data

目前,电网业务系统信息孤岛问题仍然比较严重。各业务系统对电网设备的命名、编码方法各异,同一设备在不同业务系统内的名称和编码完全不同,给多源业务系统数据的融合应用带来巨大障碍。研究不同业务系统间的设备准确关联方法具有重大价值。本文根据电网设备名称信息自身特点,研究基于SVM文本特征识别的设备关联通用算法,对各个业务系统之间的设备台账进行自动关联,并通过优化分词和特征项降维技术,提高了设备关联准确率,为多源系统间的数据融合应用提供了坚实可靠的技术基础。

The problem of Information Island in the power grid business system is much serious at present.The naming and coding methods of power grid equipment in different business systems are totally different. The names and codes of the same device in different business systems are quite different,which brings big obstacles to the application of data integration in multi-source business systems. It is of great value to study the accurate correlation method of equipment between different business systems.According to the characteristics of equipment name information in power grid business systems,general algorithm of equipment association based on SVM text feature recognition is studied. In this paper,equipment ledgers between the various business systems are automatically associated by optimizing the segmentation and feature dimension reduction technology. As results,equipment association accuracy is remarkably improved,which provides a solid and reliable foundation for the application of data fusion in multi-source business systems.