电力系统自动化2016，Vol.40Issue(23)：49-55,69,8.DOI:10.7500/AEPS20160514002
能源互联网多能扰动识别的数据流处理模型
Data Stream Processing Model for Multi-energy Disturbance Identification of Energy Internet
王德文 1李俊1
作者信息
- 1. 华北电力大学控制与计算机工程学院，河北省保定市 071003
- 折叠
摘要
Abstract
Multi-energy disturbances might occur in the process of energy production,dispatch and use owing to the integration of electrical energy,natural gas,thermal energy,and so on.Traditional disturbance detection based on off-line data can hardly meet the real-time requirements of the energy internet.Data stream technology can be used to detect multi-energy disturbance signals on line. By proceeding from the interaction between energy and information, the energy internet multi-energy disturbance problem is analyzed,and mathematical models of different disturbance signals are developed.These disturbance signals are decomposed using wavelet transform and a signal data stream processing model of disturbance signals based on a sliding window with a synoptic data structure is built first.Secondly,for the purpose of rapid updating of the outline structure, the wavelet tree updating algorithm is improved.As a result the extraction of perturbation signal features is optimized and the decision tree algorithm is used to classify these signal features.Finally,the data stream processing model built in this article is applied to the identification of power quality disturbance and gas quality disturbance to verify the validity of the data stream model.关键词
能源互联网/数据流处理/多能扰动/小波树/决策树Key words
energy internet/data stream processing/multi-energy disturbances/wavelet-tree/decision tree引用本文复制引用
王德文,李俊..能源互联网多能扰动识别的数据流处理模型[J].电力系统自动化,2016,40(23):49-55,69,8.
