Comparative Analysis of Load-Shaping-Based Privacy Preservation Strategies in a Smart Grid

Cihan Emre Kement, Hakan Gultekin, Bulent Tavli*, Tolga Girici, Suleyman Uludag

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

A key enabler for the smart grid is the fine-grained monitoring of power utilization. Although such a mechanism is helpful in the optimization of the whole electricity generation, distribution, and consumption cycle, it also creates opportunities for the potential adversaries in deducing the activities and habits of the subscribers. In fact, by utilizing the standard and readily available tools of nonintrusive load monitoring (NILM) techniques on the metered electricity data, many details of customers' personal lives can be easily discovered. Therefore, prevention of such adversarial exploitations is of utmost importance for privacy protection. One strong privacy preservation approach is the modification of the metered data through the use of on-site storage units in conjunction with renewable energy resources. In this study, we introduce a novel mathematical programming framework to model eight privacy-enhanced power-scheduling strategies inspired and elicited from the literature. We employ all the relevant techniques for the modification of the actual electricity utilization (i.e., on-site battery, renewable energy resources, and appliance load moderation). Our evaluation framework is the first in the literature, to the best of our knowledge, for a comprehensive and fair comparison of the load-shaping techniques for privacy preservation. In addition to the privacy concerns, we consider monetary cost and disutility of the users in our objective functions. Evaluation results show that privacy preservation strategies in the literature differ significantly in terms of privacy, cost, and disutility metrics.

Original languageEnglish
Article number7956260
Pages (from-to)3226-3235
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume13
Issue number6
DOIs
Publication statusPublished - Dec 2017

Keywords

  • Goal programming
  • load shaping
  • mixed-integer programming (MIP)
  • mixed-integer quadratic programming (MIQP)
  • multiobjective programming
  • nonintrusive load monitoring (NILM)
  • privacy
  • renewable energy
  • smart grid

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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