Wide area network twins for enabling energy transition by integration of different forecast databases and AI applications

The energy transition that the world is currently going through calls for sophisticated tools to achieve advanced monitoring for increased visibility. These tools should support in planning renewable integration and other system investments as well as integration of AI/ML algorithms for prediction and planned maintenance. It is also critical to access and use information from different data bases, like weather database. Similar tools have been attempted and are popular in other domains and digital twins are at the centre of these attempts. Wide area power network twins can bring the benefits of digital twins into power domain. This paper presents a framework with an intelligent ‘Wide Area Network Twin’ which enables live status updates of physical assets, system wide visualization and AI/ML based prediction and diagnostics. Communication plays a vital role to achieve the framework with all its capabilities and the framework proposed in this paper relies on IEC61850 Routable GOOSE for wide area communication. The power network under consideration is emulated in MATLAB and a proof-of-concept with advanced protection and control devices is presented. The framework itself is implemented with Python.