The use of data from residential smart meters can help in the management and control of distribution grids. This provides significant benefits to electricity retailers as well as distribution system operators but raises important questions related to the privacy of consumers' information. In this article, an innovative differential privacy (DP) compliant algorithm is developed to ensure that the data from consumer's smart meters are protected. The effects of this novel algorithm on the operation of the distribution grid are thoroughly investigated not only from a consumer's electricity bill point of view but also from a power systems point of view. This method allows for an empirical investigation into the losses, power quality issues, and extra costs that such a privacy-preserving mechanism may introduce to the system. In addition, severalcost allocation mechanisms based on the cooperative game theory are used to ensure that the extra costs are divided among the participants in a fair, efficient, and equitable manner. Overall, the comprehensive results show that the approach provides privacy preservation in line with the consumer's preferences and does not lead to significant cost or loss increases for the energy retailer. In addition, the novel algorithm is computationally efficient and performs very well with a large number of consumers, thus demonstrating its scalability.

中文翻译：

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在智能电网环境中保护智能电表数据的隐私


使用住宅智能电表的数据有助于管理和控制配电网。这为电力零售商和配电系统运营商带来了巨大的好处，但也引发了与消费者信息隐私相关的重要问题。在本文中，开发了一种创新的差分隐私 (DP) 兼容算法，以确保来自消费者智能电表的数据受到保护。这种新颖算法对配电网运行的影响不仅从消费者的电费角度而且从电力系统的角度进行了彻底的研究。该方法允许对这种隐私保护机制可能给系统带来的损耗、电能质量问题和额外成本进行实证调查。此外，采用多种基于合作博弈理论的成本分配机制，保证额外成本在参与者之间公平、高效、公平地分配。总体而言，综合结果表明，该方法提供了符合消费者偏好的隐私保护，并且不会导致能源零售商的成本或损失显着增加。此外，该新颖算法计算效率高，并且在大量消费者的情况下表现良好，从而证明了其可扩展性。