摘要
当前农村及城镇配电台区低电压问题日益严重,缺乏台区低电压状态识别方法,提出一种基于自组织特征映射网络的台区低电压状态识别模型。推导了状态识别所需的特征参量,研究了台区低电压与供电半径、导线截面积、配电变压器负载率、配电变压器档位、功率因素和三相不平衡等因素之间的关系,建立台区低电压状态识别指标体系,利用自组织特征映射网络模型根据台区低电压状态进行分类。通过与待测台区的实际验证,可以准确地解决台区低电压状态识别问题,便于供电公司提前制定相应措施,满足居民的用电需求。
Low voltage problem of distribution substation areas in the countryside and towns is becoming more and more serious,and methods for identifying low voltage state of substation areas are missing.A model for recognizing substation area low voltage status was proposed,based on a self-organizing feature map network.Characteristic parameters required for status recognition were derived,and the relationship between the substation area low voltage and power supply radius,wire cross section,distribution transformer load rate,distribution transformer gears,power factor,three-phase imbalance and other factors were studied.A recognition index system was set up for low voltage status in the substation area to use the self-organizing feature map network model to classify the low-voltage status.Actual verification in the sub-station area under test indicated that the proposed model could accurately solve the problem of identifying the low voltage status of the sub-station area and make it easy for the power supply company to formulate corresponding measures in advance,thus satisfying residents’power demand.
作者
刘明
郝思鹏
Liu Ming;Hao Sipeng(School of Electric Power,Nanjing Institute of Technology,Nanjing Jiangsu 211167,China)
出处
《电气自动化》
2020年第4期55-58,共4页
Electrical Automation
基金
国家自然科学基金(51607083)
江苏省高校自然科学研究重大项目(17KJA470003)。
关键词
配变台区
自组织特征映射网络
状态识别
低电压
特征参量
distribution substation area
self-organizing feature map network
state recognition
low voltage
characteristic parameter
