智能电网大数据的分析与应用(英文)  

Applications of Smart Grid Big Data Analytics

作　　者：高峰 刘广一[2] Chris Saunders 朱文东 陈振宇[3] 于洋[3] 

机构地区：[1]国网智研院美国研究院,Santa Clara,CA 95054 [2]中国电力科学研究院,北京市100192 [3]斯坦福大学,Palo Alto 94305

出　　处：《电力建设》2015年第10期11-19,共9页Electric Power Construction

基　　金：国家自然科学基金资助项目(51261130472);国家电网公司科技项目(DZB51201403772)~~

摘　　要：能源互联网的兴起是全球能源环境与经济发展双重压力导致的结果,这种趋势不可避免地促进大数据分析技术的快速发展。大数据技术是指从各种各样类型的海量数据中,快速获得有价值信息的技术。简要介绍了国网智研院美国研究院大数据团队的研究工作和实验室软硬件配置,介绍了智能电网数据结构和计算架构等概念性的设计。重点介绍了与斯坦福大学合作进行的用户分组分类和需求响应定量计算方法,以及非侵入式电能分解。这些工作基于集成的数据模型和开源软件技术,将为电网公司和客户同时带来收益。With the rapid progress in information technology,a novel concept—＂Energy Internet＂,that concentrates on the coordination and optimization of multi-type energy flows via advanced communication and internet technology,has received a lot of attention. The result of such an inevitable trend is that a fundamental technique—Big Data Analytics—must be developed to handle massive influx of data from multiple heterogeneous sources,as well as utilize the data to swiftly derive an economic value. The paper gives an overviewon research works conducted at SGRI North America big data lab with highlights on hardware configuration and software deployment of the cluster environment. The paper reviews several ongoing research topics performed in the lab with an emphasis on customer segmentation and response targeting（ collaboration with Stanford University）; and energy disaggregation. These works are built on an integrated power system data model that is supported by open source technology. Preliminary results showthat our research will benefit both utility companies and customers.

关 键 词：大数据解析 混合整数规划 用电行为分析 电能分解 

分 类 号：TM76[电气工程—电力系统及自动化]