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Journal ArticleDOI

Energy Big Data Analytics and Security: Challenges and Opportunities

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TLDR
New findings and developments in the existing big energy data analytics and security and several taxonomies have been proposed to express the intriguing relationships in the field.
Abstract
The limited available fossil fuels and the call for sustainable environment have brought about new technologies for the high efficiency in the use of fossil fuels and introduction of renewable energy. Smart grid is an emerging technology that can fulfill such demands by incorporating advanced information and communications technology (ICT). The pervasive deployment of the advanced ICT, especially the smart metering, will generate big energy data in terms of volume, velocity, and variety. The generated big data can bring huge benefits to the better energy planning, efficient energy generation, and distribution. As such data involve end users’ privacy and secure operation of the critical infrastructure, there will be new security issues. This paper is to survey and discuss new findings and developments in the existing big energy data analytics and security. Several taxonomies have been proposed to express the intriguing relationships of various variables in the field.

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Journal ArticleDOI

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

TL;DR: An application-oriented review of smart meter data analytics identifies the key application areas as load analysis, load forecasting, and load management and reviews the techniques and methodologies adopted or developed to address each application.
Journal ArticleDOI

Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges

TL;DR: In this paper, the authors conduct an application-oriented review of smart meter data analytics following the three stages of analytics, namely, descriptive, predictive and prescriptive analytics, identifying the key application areas as load analysis, load forecasting, and load management.
Journal ArticleDOI

Application of Big Data and Machine Learning in Smart Grid, and Associated Security Concerns: A Review

TL;DR: A comprehensive study on the application of big data and machine learning in the electrical power grid introduced through the emergence of the next-generation power system—the smart grid (SG), with current limitations with viable solutions along with their effectiveness.
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Big data privacy: a technological perspective and review

TL;DR: This paper covers uses of privacy by taking existing methods such as HybrEx, k-anonymity, T-closeness and L-diversity and its implementation in business and presents recent techniques of privacy preserving in big data.
Journal ArticleDOI

Big data issues in smart grid – A review

TL;DR: In this article, the authors present a holistically overview on the state-of-the-art of big data technology in smart grid integration, which also contains some brand new applications with the latest big data technologies.
References
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Journal ArticleDOI

False data injection attacks against state estimation in electric power grids

TL;DR: In this article, a new class of attacks, called false data injection attacks, against state estimation in electric power grids is presented and analyzed, under the assumption that the attacker can access the current power system configuration information and manipulate the measurements of meters at physically protected locations such as substations.
Book ChapterDOI

Conjunctive, subset, and range queries on encrypted data

TL;DR: This work constructs public-key systems that support comparison queries on encrypted data as well as more general queries such as subset queries (x∈ S) and supports arbitrary conjunctive queries without leaking information on individual conjuncts.
Posted Content

Conjunctive, Subset, and Range Queries on Encrypted Data.

TL;DR: In this paper, a general framework for constructing and analyzing public-key systems supporting conjunctive queries on encrypted data has been presented, without leaking information on individual conjuncts.
Journal ArticleDOI

Malicious Data Attacks on the Smart Grid

TL;DR: Malicious attacks against power systems are investigated, in which an adversary controls a set of meters and is able to alter the measurements from those meters, and an optimal attack based on minimum energy leakage is proposed.
Journal ArticleDOI

Short-Term Load Forecasting Methods: An Evaluation Based on European Data

TL;DR: In this article, a comparison of univariate methods for forecasting up to a day-ahead of electricity demand data from ten European countries is performed using intraday electricity demand from 10 European countries as the basis of an empirical comparison.
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