Fine-grained energy usage data collected by Smart Meters (SM) is one of the key components of the smart grid (SG). While collection of this data enhances efficiency and flexibility of SG, it also poses a serious threat to the privacy of consumers. Through techniques such as nonintrusive appliance load monitoring (NALM), this data can be used to identify the appliances being used, and hence disclose the private life of the consumer. Various methods have been proposed in the literature to preserve the consumer privacy. This paper focuses on load shaping (LS) methods, which alters the consumption data by means of household amenities in order to ensure privacy. An overview of the privacy protection techniques, as well as heuristics of the LS methods, privacy measures, and household amenities used for privacy protection are presented in order to thoroughly analyze the effectiveness and applicability of these methods to smart grid systems. Finally, possible research directions related to privacy protection in smart grids are discussed.

中文翻译：

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智能电网中基于负载整形的隐私保护：概述

Smart Meters (SM) 收集的细粒度能源使用数据是智能电网 (SG) 的关键组成部分之一。收集这些数据在提高 SG 的效率和灵活性的同时，也对消费者的隐私构成了严重威胁。通过非侵入式设备负载监控 (NALM) 等技术，这些数据可用于识别正在使用的设备，从而揭示消费者的私人生活。文献中提出了各种方法来保护消费者隐私。本文重点介绍负载整形（LS）方法，该方法通过家庭设施改变消费数据以确保隐私。隐私保护技术的概述，以及 LS 方法的启发式方法、隐私措施、以及用于隐私保护的家庭设施，以彻底分析这些方法对智能电网系统的有效性和适用性。最后，讨论了与智能电网隐私保护相关的可能研究方向。