Representing Decision-Makers in SGAM-H: The Smart Grid Architecture Model Extended with the Human Layer

Abstract

The safety and security of critical infrastructures is both a technical and a social issue. However, most risk analysis methods focus predominantly on technical aspects and ignore the impact strategic human decisions have on the behavior of systems. Furthermore, the high degree of complexity and lack of historical data for probability estimations in case of new and emerging systems seriously limit the practical utility of traditional risk analysis methods. The Conflicting Incentives Risk Analysis (CIRA) method concentrates on human decisionmakers to address these problems. However, the method's applicability is restricted by the fact that humans are not represented in the Smart Grid Architecture Model (SGAM) which is the industry's most well-known model of the Smart Grid ecosystem. Therefore, the main objective of this paper is to establish a connection between CIRA and SGAM by proposing the SGAM-H, an enhanced version of the original architecture model complemented by the Human Layer. The development and evaluation of the artifact is guided by the Design Science Research methodology. The evaluation presents a working example of applying the CIRA method on a scenario involving intra-organizational risks at a Distribution System Operator. The key benefit of the SGAM-H is that it enables the construction of a common understanding among stakeholders about risks related to key decision-makers, which is a fundamental first step towards forming a more complete picture about potential issues affecting the electric grids of the future.

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

“…Understanding the role of insider threats [22,49] and human factors [50,51] in smart-grid cybersecurity is an emerging area of research. These studies investigate the impact of human behavior [52,53], social engineering [54,55], training and awareness programs [56,57], and policy frameworks to address the human element in cybersecurity [58,59]. Given the large amount of data generated by smart grids, the research has focused on secure data management, privacy-preserving techniques, and anonymization approaches to protect sensitive information while enabling data analysis for grid optimization and energy management [60,61].…”

The (still unexplored) social side of smart grid development

“…To cope with this complexity, the knowledge, and data must be provided in a standardized way [2,7]. In the Smart Grid area, the SGAM together with the IEC 62559-2 Use Case Methodology for Requirements Engineering [15] is the common standardization tool [13]. The central intention is to bring different elements and systems in consistency.…”

“…Research has already started to draw attention to the need of considering stakeholders because of their neglect in the SGAM. Previous research [13] suggests the integration of human decisionmakers, which are not represented in SGAM. By combining CIRA, a risk analysis method, and SGAM, the authors present an additional human layer (SGAM-H).…”

Challenges in the representation of digital applications in SGAM: Overview and solutions

“…This finding is also shown in the EU Bridge project [12], where the importance of digital applications and data privacy is highlighted within the smart grids context. Furthermore, in [13], a modified version of SGAM was proposed to highlight the relevance of human decisions, separating human actors from the rest of entities reflected in SGAM. In addition, the approach shown by [14] describes the need of considering computational models within SGAM to achieve a coordinated view of issues such as control, optimization, and data analytics.…”