摘要
分析了电力系统短期负荷预测的特点及影响负荷预测准确性的相关因素。阐述了传统负荷预测方法存在的不足及将大数据系统引入负荷分析过程中的优势,将传统负荷方法与大数据分析相结合,可在进行负荷分析的同时利用大数据技术将各项影响因素与大数据进行比对,减小误差提高负荷预测精度,为电力系统进行短期负荷预测提供借鉴。
This paper analyzes the characteristics of short-term load forecasting of power systems and the related factors affecting the accuracy of load forecasting.The deficiency of the traditional load forecasting methods and the advantages of introducing large data system into the load analysis process are analyzed.By combining the traditional load method with large data analysis,the big data technology can be used to compare various influencing factors with large data while performing load analysis,reduce errors and improve the load forecasting precision,providing a reference for short-term load forecasting of power systems.
作者
闫群民
邱绎同
杨浩
王建东
YAN Qunmin;QIU Yitong;YANG Hao;WANG Jiandong(School of Electric Power Engineering,Shaanxi University of Technology,Hanzhong 723000,China)
出处
《电工技术》
2020年第5期16-18,共3页
Electric Engineering
基金
2019年国家级大学生创新创业计划训练项目(编号201910720012)。
关键词
大数据
负荷预测
模型
big data
load forecasting
model
