Conversion of CIM CGMES data sets to the open source software pandapower – case study including an ENTSO-E test network

The need for information and data exchange between multiple grid operators is more important than ever before. In Europe, the “Common Grid Model Exchange Standard” (CGMES) by the “European Network of Transmission System Operators for Electricity” (ENTSO-E) is one of the standard data formats to exchange grid data. Even though CGMES is well defined, it allows for ambiguities, small variations of modelling and interpretation of different grid assets, which can result in errors and wrong power flow results since different applications might interpret the CGMES data differently. A direct intuitive interpretation and validation of CGMES data sets by humans or free available grid analysis tools is barely possible due to their storage in long Extensible Markup Language (XML) files. Thus, a conversion into a simpler, human-readable and open source format is required. In this work, the open source Python package “cim2pp” is introduced, for converting CGMES data sets into the open source grid format “pandapower”. The converter’s accuracy is shown by translating two benchmark data sets, including a reference grid model from ENTSO-E. Additional performance tests demonstrate that cim2pp converts large data sets to pandapower within acceptable computation times.