计算机工程2017，Vol.43Issue(4)：8-14,7.DOI:10.3969/j.issn.1000-3428.2017.04.002
基于Storm的电网时间序列数据实时预测框架
Real-time Predication Framework for Power Grid Time-series Data Based on Storm
摘要
Abstract
This paper researches on the real-time predication of power grid Time-series Data(TSD) and puts forward a predication framework based on Storm platform and Autoregressive Integrated Moving Average(ARIMA) model.It analyzes the characteristics of different types of power grid TSD and presets fitting model to reduce the blindness of model building and to shorten the time of predication.Meanwhile,it designs a new storage mode for TSD based on HBase to accelerate the speed of data retrieval.It compares the influences of different data samples on the results of predication and analyzes the prediction error in real time through the concurrent prediction of massive TSD sources.Finally,three aspects including prediction precision,computing speed and resource occupancy are chosen to verify the effectiveness and practicability of the proposed framework by authentic cases.关键词
时间序列数据/实时预测/Storm平台/自回归积分移动平均模型/电网/大数据Key words
Time-series Data(TSD)/real-time predication/Storm platform/Autoregressive Integrated Moving Average(ARIMA) model/power grid/big data分类
信息技术与安全科学引用本文复制引用
吴克河,朱亚运,李皓阳,李权..基于Storm的电网时间序列数据实时预测框架[J].计算机工程,2017,43(4):8-14,7.基金项目
中央高校基本科研业务费专项资金(2015XS72). （2015XS72）
