AMI Smart Meter Big Data Analytics for Time Series of Electricity Consumption

被引:20
作者
Rashid, Mohammad Harun [1 ]
机构
[1] Pace Univ, New York, NY 10038 USA
来源
2018 17TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (IEEE TRUSTCOM) / 12TH IEEE INTERNATIONAL CONFERENCE ON BIG DATA SCIENCE AND ENGINEERING (IEEE BIGDATASE) | 2018年
关键词
Smart meter; AMI; smart grid; time series; big data; electric consumptions; forcast; data analytics; load profile;
D O I
10.1109/TrustCom/BigDataSE.2018.00267
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
AMI Smart meters are the advanced meters capable of measuring customer energy consumption at a fine-grained time interval, e.g., every 5 minutes, 15 minutes etc. The data are very sizable, and might be from different sources, along with the other social-economic metrics, which make the data management very complex. A smart grid is an intelligent electricity grid that optimizes the generation, distribution and consumption of electricity through the introduction of Information and Communication Technologies on the electricity grid. Deployment of smart grids gives space to an occurrence of new methods of machine learning and data analysis. Smart grids can contain a millions of smart meters, which produce a large amount of data of electricity consumption (long time series). Big Data technologies offers suitable solutions for utilities. This paper presents a thorough analysis of 5-minutes 100 anonymized commercial buildings meter data sets to explore time series of electricity consumption and on the creation of a simple forecast model, which uses similar day approach. Our big data analytics can help energy companies to improve the management of energy and services, support intelligent grid control, make an accurate forecast or to detect anomalies.
引用
收藏
页码:1771 / 1776
页数:6
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