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  • Cited by 2
  • Print publication year: 2016
  • Online publication date: December 2015

8 - Big data processing for smart grid security

from Part II - Big data over cyber networks

Summary

The development of the smart grid, impelled by the increasing demand from industrial and residential customers together with the aging power infrastructure, has become an urgent global priority due to its potential economic, environmental, and societal benefits. Smart grid refers to the next-generation electric power system that aims to provide reliable, efficient, secure, and quality energy generation, distribution, and consumption, using modern information, communications, and electronics technology. A distributed and user-centric system will be introduced in smart grid, which will incorporate end consumers into its decision processes to provide a cost-effective and reliable energy supply. In the smart grid, the modern communication infrastructure will play a vital role in managing, controlling, and optimizing different devices and systems. Information and communication technologies will provide the power grid with the capability of supporting two-way energy and information flows, rapid isolation, and restoring of power outages, facilitating the integration of renewable energy sources into the grid and empowering the consumer with tools for optimizing their energy consumption. The introduction of the cyber infrastructure needed to realize the smart grid also brings with it vulnerability to security breaches. Thus security is amajor concern in the development of the smart grid. Moreover, the widespread deployment of smart meters and sensors such as phasor measurement units results in the generation of massive amounts of data that can be exploited in optimizing and securing the grid. This chapter addresses these two issues by investigating the applications of big data processing techniques for smart grid security from two perspectives: exploiting the inherent structure of the data, and dealing with the huge size of the data sets. Two specific applications are included in this chapter: sparse optimization for false data injection detection, and a distributed parallel approach for the security constrained optimal power flow problem.

Preliminaries and motivations

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