基于CIM的智能电网图模型访问控制建模

Ivana Kovacevic, A. Erdeljan, Miroslav Zarić, Nikola Dalčeković, I. Lendák
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引用次数: 0

摘要

根据美国能源情报署(EIA)的数据,电力消费已经增长,而且这种趋势将持续下去。大多数现代配电网络,演变成智能电网,通过复杂的软件管理,如先进的配电管理系统(ADMS)。它们的操作是基于对来自配电网中不同设备的数据的收集、分析和转换。智能电网的数据量正在快速增长。因此,处理不断增长的数据量可能会给关系数据库带来重大挑战,因为它们可能会与执行复杂查询的需求作斗争。在某些情况下,例如在电力系统网络建模中,数据模型自然地由图形表示,因此图形数据库可以提供可行的、更有效的替代方案。本文提出了一种在面向图的数据库中包含敏感数据访问权限的方法,使我们能够决定谁可以访问敏感数据,谁不能。我们对安全控制进行了分析,以限制对个人数据的访问,使用来自欧洲现有配电公用事业网络模型的现实数据模型,但所描述的方法也适用于其他敏感数据。我们得出的结论是,建议的方法将提供实现访问管理安全控制的能力,而每种方法将以不同的方式影响整体系统性能的级别。
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Modelling access control for CIM based graph model in Smart Grids
Consumption of electricity has grown, and that tendency will continue according to Energy Information Administration (EIA). Most modern distribution networks, evolving into Smart Grids, are managed through sophisticated software, such as advanced distribution management systems (ADMS). Their operations are based on gathering, analysis and transformation of data coming from the different devices in distribution network. Data volume in Smart Grids is increasing rapidly. Therefore, handling that growing amount of data may pose significant challenges for relational databases in the future, as they may struggle with demand for execution of complex queries. In some cases, like in modeling power system network, the data model is naturally represented by a graph, hence graph databases could provide viable, more efficient alternative. The paper is proposing an approach to include sensitive data access permissions in a graph oriented database – enabling us to decide who can access the sensitive data and who cannot. We have performed analysis on security controls to limit the access to personal data using a realistic data model derived from an existing network model of power distribution utility based in Europe, but described approach is also applicable to other sensitive data. We concluded that the proposed approach would provide ability for implementing access management security controls, while each approach would differently affect the levels of overall system performances.
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