Abstract
In order to evaluate the effectiveness of innovative services and technologies spanning over the ICT-enabled power system, realistic models are required. Although nowadays there is a wide range of power system data models, these models do not include a lifelike representation of the ICT system architecture and do not consider the level of interconnectedness of the two systems. In this paper, we propose a methodology for quantification of the geospatial relations between ICT and power system based on openly available data. We describe a graph-theoretic approach, formulate a problem of assessing geospatial relations and discuss the methods required to process publicly available data, retrieve scenarios for different regions and quantify the level of interdependence between ICT and power system.
Highlights
With the growing penetration of distributed generators and renewable energy sources, the introduction of virtual power plants and the subsequent need for coordination of distributed smart power system components, the role of the Information and Communication Technology (ICT) becomes indispensable
Nowadays there is a wide range of power system data models, these models do not include a lifelike representation of the ICT system architecture and do not consider the level of interconnectedness of the two systems
We propose a methodology for quantification of the geospatial relations between ICT and power system based on openly available data
Summary
With the growing penetration of distributed generators and renewable energy sources, the introduction of virtual power plants and the subsequent need for coordination of distributed smart power system components, the role of the Information and Communication Technology (ICT) becomes indispensable. In order to evaluate the reliability and effectiveness of these services, analytical and simulation-based techniques are usually applied to representative evaluation scenarios, which describe the composition and dependencies between components of the system. Such evaluation scenarios have to take the spatial properties and interdependencies of the real infrastructures into account. While geospatial interdependencies have been identified as one of the key dependency types
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