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

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

*المؤلف المقابل لهذا العمل

نتاج البحث: المساهمة في مجلةArticleمراجعة النظراء

24 اقتباسات (Scopus)


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.

اللغة الأصليةEnglish
رقم المقال7956260
الصفحات (من إلى)3226-3235
عدد الصفحات10
دوريةIEEE Transactions on Industrial Informatics
مستوى الصوت13
رقم الإصدار6
المعرِّفات الرقمية للأشياء
حالة النشرPublished - ديسمبر 2017

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