The integration of ICT into power systems has increased the interdependencies between the two systems. The operation of power system depends on several ICT-enabled grid services which manifest the interdependencies. ENTSO-E system state classification is a tool that is widely used by operators to determine the current operational state of the power system. However, it does not adequately describe the impact of ICT disturbances on the operation of the power system. Despite their interconnections, the operational states of both systems have been described separately so far. This paper bridges the well-established ENTSO-E systems state classification with an ICT system state classification, forming a new model considering the state classification of the ICT-enabled grid services. The model is developed by first identifying the ICT-enabled services, remedial actions and the respective performance requirements that are required by the power system. Then the states of these services are specified based on the supporting ICT system. The resulting joint state description shows how performance degradation of ICT-enabled services (introduced by disturbances) can affect the operation of the interconnected power system. Two case studies of such ICT-enabled services, namely state estimation and on-load tap changer control, are investigated in terms of how their operational states affect the states of the power system. A third case study highlights the interdependencies that exist between the services. These case studies demonstrate the interdependencies that exist between power and ICT systems in modern cyber-physical energy systems, thus highlighting the usage of a unified system state description.

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Increasing interdependencies between power and ICT systems amplify the possibility of cascading failures. Resilience against such failures is an essential property of modern and sustainable power systems and networks. To assess the resilience and predict the behaviour of a system consisting of interdependent subsystems, the interconnection requires adequate modeling. This work presents an approach to model and determine the state of these so-called interconnectors in future cyber-physical energy systems with strongly coupled ICT and power systems for a resilience analysis. The approach can be used to capture the impact of various parameters on system performance upon suitable modification. An hierarchical modeling approach is developed with atomic models that demonstrate the interdependencies between a power and ICT system. The modeling approach using stochastic activity nets is applied to an exemplary redispatch process in a cyber-physical energy system. The performance of an interconnector when facing limited performance from the ICT subsystem and its subsequent impact on the power system is analysed using the models. The state of the interconnector, as well as the service level are mapped to a resilience state-space diagram. The representation of system state on the resilience state-space diagram allows interpretation of system performance and quantification of resilience metrics.

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The rising importance and efficiency of Artificial Intelligence (AI) has led to AI being substantially deployed in various domains and its usage growing rapidly. For the smart grid, adopting AI-based methods has transformed established power system functions into more advanced analogs. However, the unstable operation of AIbased services may misguide operators to make incorrect operational decisions leading to substantial consequences. Accordingly, the rapidly growing market of AI-based services calls for raising awareness of accountability of these services. Accountability in grid services is getting even more challenging with respect to the wide availability of the AI-based methods implemented as libraries and the emergence of AI as a service.A key way forward is through smart grid operators monitoring their AI-based services to enable accountability. Accountable AI increases trustworthiness and accelerates acceptance of these services by society. Toward this, a conceptual representation of a monitoring regime for AI-based services is proposed and major challenges to realising it are identified. In addition, this work aims to draw more attention to AI-based services and the issues they raise, given AI increasing prominence and the general calls for the more responsible and accountable use of AI. CCS CONCEPTS• Security and privacy → Social aspects of security and privacy; • Applied computing → Investigation techniques.