电测与仪表2025，Vol.62Issue(7)：38-48,11.DOI:10.19753/j.issn1001-1390.2025.07.005
面向新型电力系统大数据的负载标记方法研究
Research on load labeling method for big data in novel power system
摘要
Abstract
The power grid is rapidly becoming highly informationized and automated,and the scale of data genera-ted is also rapidly expanding.However,one of the main obstacles to the effective use of power big data is the lack of efficient data labeling methods.By proposing a flexible framework to mark load patterns and usage habits in a non-intrusive way,the composite data tag file is used for smart grid functions such as demand response,energy management and load monitoring.The data is automatically preprocessed using signal processing techniques such as matched filter.The generation of data marker files is realized by using two key constructions,namely,the genera-tive adversary network and the kernel density estimator.In addition,various components in these structures are op-timized to ensure the stability of the learning process.Unique evaluation indicators are also identified to measure the performance of the composite dataset.The synthetic dataset is compared with the real dataset,and the smart grid machine learning algorithm is trained and tested on this basis.The simulation results verify the effectiveness of the proposed method.关键词
电力大数据/数据标记/新型电力系统Key words
power big data/data marking/novel power system分类
信息技术与安全科学引用本文复制引用
张喜铭,徐欢,杨秋勇..面向新型电力系统大数据的负载标记方法研究[J].电测与仪表,2025,62(7):38-48,11.基金项目
中国南方电网有限责任公司数据资产管理技术服务项目(0000002022030304XX00048) （0000002022030304XX00048）
