Online and scalable data validation in advanced metering infrastructures
Paper in proceedings, 2014

The shift from traditional to cyber-physical grids involves the deployment of Advanced Metering Infrastructures, networks of communication-enabled devices remotely controlled by utilities. Live information collected by these devices enables for applications such as demand/response, real-time pricing or intrusion detection, among others. In these scenarios, data validation is necessary in order to preprocess the noisy and lossy data produced by the devices and make it available to utilities' or third parties' applications. Challenges proper of data validation in this domain include the possibility of expressing validation rules specific to an Advanced Metering Infrastructure installation and analysis techniques that cope with the large and fluctuating volume of data produced by the devices. In this paper, we discuss and provide evidence of the online, scalable and expressive validation analysis enabled by the data streaming processing paradigm. Based on a prototype implementation on top of the Storm processing engine and using data from a real-world Advanced Metering Infrastructure, we show that streaming-based validation rules enable for the analysis of thousands of meters per second and only incur in small latency penalties in the order of milliseconds.

Data Validation

Data Streaming

Advanced Metering Infrastructures

Author

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Magnus Almgren

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Marina Papatriantafilou

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

IEEE PES Innovative Smart Grid Technologies Conference Europe; 12-15 Oct. 2014 Istanbul

Vol. 2015-January January

Subject Categories

Computer Science

Computer Vision and Robotics (Autonomous Systems)

DOI

10.1109/ISGTEurope.2014.7028740

ISBN

9781479977215

More information

Created

10/7/2017