DocumentCode :
665247
Title :
Advanced analytics for harnessing the power of smart meter big data
Author :
Alahakoon, D. ; Xinghuo Yu
Author_Institution :
Sch. of Inf. & Bus. Analytics, Deakin Univ., Warum Ponds, VIC, Australia
fYear :
2013
fDate :
14-14 Nov. 2013
Firstpage :
40
Lastpage :
45
Abstract :
Smart meters or advanced metering infrastructure (AMI) are being deployed in many countries around the world. Smart meters are the basic building block of the smart grid and governments have invested vast amounts in smart meter deployment targeting wide economic, social and environmental benefits. The key functionality of the smart meter is the capture and transfer of data relating to the consumption (electricity, gas) and events such as power quality and meter status. Such capability has also resulted in the generation of an unprecedented data volume, speed of collection and complexity, which has resulted in the so called big data challenge. To realize the hidden value and power in such data, it is important to use the appropriate tools and technology which are currently being called advanced analytics. In this paper we define a smart metering landscape and discuss different technologies available for harnessing the smart meter captured data. Main limitations and challenges with existing techniques with big data are also highlighted and several future directions in smart metering are presented.
Keywords :
Big Data; data analysis; power consumption; power engineering computing; smart meters; smart power grids; AMI; advanced analytics; advanced metering infrastructure; data capturing; electricity consumption; gas consumption; power harnessing; power quality; smart grid; smart meter Big Data; Data handling; Data storage systems; Electricity; Information management; Real-time systems; Smart grids; Advanced Metering Infrastructure (AMI); Analytics; Big Data; Data Mining; Smart Meters; Stream Analytics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Energy Systems (IWIES), 2013 IEEE International Workshop on
Conference_Location :
Vienna
Type :
conf
DOI :
10.1109/IWIES.2013.6698559
Filename :
6698559
Link To Document :
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