Trust How can the trustworthiness of components, data, and services in cyber-physical systems be evaluated to enable better prediction of events and decision-making?
The digitalization of energy systems has led to cyber-physical energy systems (CPESs), characterized by increased penetration of information and communication technologies (ICT). ICT systems typically comprise hardware, software, and data, all of which enable the safe and reliable operation of the interconnected energy system. This growing dependence on ICT systems has already increased the number of factors affecting the overall behaviour of CPESs. Past events have demonstrated that, in addition to traditional power system problems, ICT issues such as software bugs, congestion, and cyber threats can result in large-scale blackouts. This underscores the need for holistic monitoring not only of the power system but also of the interconnected ICT system to detect events that can harm the entire CPES.
Trust in the Context of Cyber-Physical Energy Systems
Trust, a concept originally from the field of organic computing, is used to assess the trustworthiness of components and subsystems. It is defined as a "context-dependent and multivariate sense about an entity with different facets such as functional correctness, safety, security, reliability, credibility, and usability." Trust can pertain to components, data, or services of the energy and ICT systems. Not all facets are relevant for all entities, and the definition could be extended to consider additional facets of interest.
The trust in an entity can be assessed based on a combination of static information (e.g., from an information security management system (ISMS)), real-time information from monitoring systems (e.g., from an ICT health monitoring system or an intrusion detection system (IDS)), or based on experience. Different information contributes to the calculation of different facets. For example, an ICT health monitoring system can contribute to functional correctness, while an IDS can contribute to security. The different facets enable the use of trust to identify or anticipate a wide range of disturbances in CPESs, based on which better operational decisions can be made.
The trust in components can also be used for holistic health monitoring of the entire CPES, considering not only traditional electrical parameters (e.g., power, currents) but also non-technical parameters (e.g., the performance of ICT components and grid services). The hierarchical structure of a power system also facilitates hierarchical trust assessment. This is illustrated in the following Figure, which shows the flow of electrical measurements at three different levels. At the process level, sensors provide measurements such as active power (P), reactive power (Q), and currents (I). These measurements are then sent to an aggregator at the substation level, which collects the measurements from the sensors and sends the packaged measurements to a SCADA system at the control room level.
The first trust assessment of the sensors and their measurements is conducted at the aggregator using information from an IDS, an ISMS, and an ICT health monitoring system. As a result, the trust data transmitted to the SCADA system represents a multivariate value that can capture various disturbances, such as cyberattacks and software/hardware malfunctions. In the SCADA system, a second trust assessment is performed, considering the trust in the aggregator. This is based on inputs from the same trust sources, which can monitor not only the sensors but also the aggregator. Since the measurements from the sensors flow through the aggregator, the trust in the aggregator will encompass the trust in the sensors. This leads to a propagation of trust across different components in the CPES. The outcome of the trust assessment can then be integrated into the services (e.g., state estimation) running in the SCADA control room, resulting in better situational awareness and operational decisions in CPESs. A demonstration of trust assessment for power and ICT systems considering the state estimation service can be found at https://youtu.be/3hwi49sfllQ.
The main benefits of using trust in CPESs can be summarized as follows:
- Enhanced situational awareness: Trust and its facets provide a holistic model for monitoring power and ICT systems, considering the underlying components and data.
- Anticipation and detection of disturbances: The facets of trust can capture as well as predict a wide range of power and ICT disturbances.
- Better decision-making: The trustworthiness of components and data, when integrated into the control of CPESs, can enable better decision-making, considering not only the measurements but also their trustworthiness.
Research Questions
In this context, the ROC group focuses —without being limited to— the following research questions:
- How to assess the trust in components and services in CPESs and integrate this information into control room applications or digital twins, respectively?
- How to model and analyse the propagation of trust across different components and services in complex CPESs?
- How to semantically interpret complex multivariate trust values?
Persons
- Dr. Michael Brand (Contact person)
- Anand Narayan (Contact person)
Publications
- Framework for the Integration of ICT-relevant Data in Power System Applications
- Trust in Power System State Variables based on Trust in Measurements
- Demo abstract: A Platform to Assess the Trust in Power System Components, Data, and Services
- Assess: anomaly sensitive state estimation with streaming systems
- ASSESS – Anomaliesensitive State Estimation mit Streaming Systemen in Smart Grids
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Projects
Publications
2024
Applying Trust for Operational States of ICT-Enabled Power Grid Services
Michael Brand, Anand Narayan, Sebastian Lehnhoff; April / 2024
Modelling the propagation of properties across services in cyber-physical energy systems
Anand Narayan, Michael Brand, Nils Huxoll, Batoul Hage Hassan, Sebastian Lehnhoff ; March / 2024
Poster Abstract: A Digital Twin Platform Applied to Hydrogen Electrolyzers
AMIT KUMAR SINGH, JELKE WIBBEKE, AMIN RAEISZADEH, NILS HUXOLL, MICHAEL BRAND; DACH+ Conference on Energy Informatics 2024; October / 2024
Resilience Quantification of Interdependent Power and ICT Systems using Operational State Classification
Anand Narayan; July / 2024
2023
ASSESS – Anomaliesensitive State Estimation mit Streaming Systemen in Smart Grids
Michael Brand; December / 2023
Assess: anomaly sensitive state estimation with streaming systems
Brand, Michael and Engel, Dominik and Lehnhoff, Sebastian; Energy Informatics; 2023
Demo Abstract: IT Platform for Provision of Ancillary Services from Distributed Energy Resources
Payam Teimourzadeh Baboli, Amin Raeiszadeh, Michael Brand, and Sebastian Lehnhoff; DACH+ Conference on Energy Informatics, Vienna, Austria; 2023
Impact of ICT Latency, Data Loss and Data Corruption on Active Distribution Network Control
Klaes, Marcel and Zwartscholten, Jannik and Narayan, Anand and Lehnhoff, Sebastian and Rehtanz, Christian; IEEE Access; 2023
Poster Abstract: Algorithms for Condition Monitoring of Complex Power Electronic Systems in Photovoltaics
Loeffler, Dominik; Abstracts of the 12th DACH+ Conference on Energy Informatics 2023; October / 2023
Poster abstract: modeling of resilient state estimation in cyber-physical energy systems
Hage Hassan, Batoul and Brand, Michael and Lehnhoff, Sebastian; Abstracts of the 12th DACH+ Conference on Energy Informatics; 2023
