Abstract

Modern power systems, referred to as cyber-physical energy systems (CPESs), are complex systems with strong interdependencies between power and information and communication technology (ICT) systems. CPESs also have dependencies between the essential grid services. For instance, coordinated voltage control depends on state estimation, which depends on measurement acquisition. Since the operation of CPESs is largely influenced by these grid services, assessing their performance is crucial for assessing the performance of a CPES. Most of these grid services are enabled by the ICT system, i.e., they rely to a high degree on ICT. Hence, properties such as availability, correctness and timeliness, which depend on the involved software, hardware and data of the ICT system, must be considered for assessing the performance of an ICT-enabled grid service. Disturbances and repairs in CPESs impact these properties, which can then propagate and affect the performance of a grid service as well as other dependent grid services. There is, therefore, a need to model the influence of the properties of software, hardware and data on ICT-enabled grid services for single services as well as across several services, resulting in a propagation of these parameters. Current literature lacks such a model, which can used not only to investigate but also to visualise the impact of these properties on the overall perfromance of a grid service as well as other dependent grid services. This paper proposes a meta model for assessing the performance of ICT-enabled grid services, which can be instantiated for different grid services considering their dependencies. A multi-dimensional operational state space, which serves as a visualisation of the performance of grid services in terms of their state trajectory, is also proposed in this paper. The contributions are then demonstrated by a case study with a state estimation service and the widely-used CIGRE medium voltage benchmark power grid augmented with an ICT system. Three scenarios with disturbances are presented to show the benefits of the contributions. Specifically, the performance of the state estimation service considering the disturbances is investigated using the meta model, and the change in performance is visualised as trajectories using the operational state space. These contributions enable new possibilities for planning and vulnerability analyses: property changes in parts of the ICT system can be simulated to investigate their consequences throughout the ICT-enabled grid services. A trajectory representing their performance can then be visualized in the state space based on which measures could be implemented to potentially improve the resilience of the service against the considered disturbances.

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