基于数据驱动的拓扑识别技术在台区负荷调控的应用

Application of Data-driven Topology Recognition Technology in Substation Load Regulation

随着新型电力系统的快速发展,分布式新能源和新型用电负荷在智能配电台区中的占比增加,给低压配用电系统精细化运行带来了极大挑战。为此,系统梳理了现阶段负荷调控的典型分类及调控需求,讨论其优缺点、适用性及实施难点,提出了一种基于数据驱动的低压台区负荷调控框架。通过对智能采集装置提供的智能传感设备与量测设备数据进行感知处理,并融合拓扑识别技术,解决获取准确的户变关系难的问题。结果表明,基于数据驱动的拓扑识别技术有助于低压台区实施负荷精细化调控,支撑新型电力系统安全稳定运行。

With the rapid development of new power systems,the proportion of distributed new energy and new electricity loads in intelligent distribution areas has increased,posing great challenges to the refined operation of low-voltage distribution systems.To this end,the system sorted out the typical classifications and regulatory requirements of current load regulation,discussed their advantages and disadvantages,applicability,and implementation difficulties,a data-driven framework for low-voltage substation load regulation was proposed.By perceiving and processing the data of intelligent sensing and measuring devices provided by intelligent collection devices,and integrating topology recognition technology,the problem of obtaining accurate user variable relationships was solved.The results indicate that data-driven topology recognition technology is helpful for implementing fine load regulation in low voltage power stations and supporting the safe and stable operation of new power systems.