Automated Model Transformation for Cyber-Physical Power System Models
Abstract: Standardized information and mathematicalmodels, which model the characteristics of the power generationand power transmission systems, are requirements for futuredevelopment and maintenance of different applications tooperate the electrical grid. Available databases such as Nordpoolprovides large amounts of data for power supply and demand .The typical misconception with open availability of data is thatexisting power system software tools can interact and process thisdata. Difficulties occur mainly because of two reasons. The firston is the amount of data produced. When the topology of theelectrical grid changes e.g. when a switch opens or closes, the flowof electrical power changes. This event produce changes ingeneration, transmission and distribution of the energy anddifferent data sets are produced. The second problem is therepresentation of information . There are a limited number ofsoftware tools that can analyze this data, but each software toolrequires a specific data format structure to run. Dealing withthese difficulties requires an effective way to transform theprovided data representation into new data structures that canbe used in different execution platforms. This project aims tocreate a generic Model-to-Text (M2T) transformation capable oftransforming standardized power system information modelsinto input files executable by the Power System Analysis Tool(PSAT). During this project, a working M2T transformation wasnever achieved. However, missing functionality in someprograms connected to sub processes resulted in unexpectedproblems. This led to a new task of updating the informationmodel interpreter PyCIM. This task is partially completed andcan load basic power system information models.
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