电测与仪表2024，Vol.61Issue(4)：93-99,7.DOI:10.19753/j.issn1001-1390.2024.04.014
基于边缘计算的台区短期负荷预测方法
Short-term substation load forecasting method based on edge computing
摘要
Abstract
Distribution substation is an important link between distribution IoT and user interaction,and the substation short-term load forecasting is of great significance for achieving the lean management of the distribution Internet of Things.In order to alleviate the communication pressure caused by uploading load data from all substations,this paper proposes a short-term substation load forecasting method based on edge computing.The 30-day historical load data stored by the intel-ligent distribution terminal is used as sample data,and the sample data is cleaned using Nadaraya-Watson method.Due to the small amount of sample data,it is considered to normalize the sample and split it into standard unit curves and base value.Then,PCC matrix of historical load data is constructed,and the unit curve of similar days is obtained through re-placing the affine propagation(AP)similarity matrix with the correlation coefficient matrix,the unit curve of the similar day is obtained by clustering,and the unit curve of the test day is obtained through weighted summation.At the same time,forecast the base value of the test day and ultimately obtain the load curve of the test day.The historical load data of a distribution substation in Shandong Province for 30 days show that the proposed method can achieve reasonable predic-tion under the condition of small load magnitude,small sample and large fluctuation,and it occupies less computing re-sources in the main station.It has a positive significance for the lean operation and maintenance of the distribution net-work.关键词
配电物联网/智能终端/短期负荷预测/仿射传播聚类/数据挖掘Key words
distribution IoT/intelligent terminal/short-term load forecasting/affine propagation/data mining分类
信息技术与安全科学引用本文复制引用
张明泽,栾文鹏,艾欣,刘博..基于边缘计算的台区短期负荷预测方法[J].电测与仪表,2024,61(4):93-99,7.基金项目
国家电网有限公司科技项目(520600230011) （520600230011）
