Energy Data and Visualization

Worldwide data volume is increasing in the course of digitalization. As in other areas the energy sector is producing growing amounts of available data. This can be attributed in part to an increase of installed measurement infrastructure, but also due to publicly accessible data sets. The visualization of data is a central component when it comes to making information usable, drawing conclusions and being able to initiate measures. With the help of suitable visualization techniques, results and correlations can be presented in a way that is comprehensible to human observers. Through a uniform understanding of complex data sets, transparency can be created within projects, companies or in society.

The energy sector produces diverse and extensive data sets within which complex interrelationships must be processed and interpreted. These include, for example:

  • Georeferenced data, such as networks and grids (electricity, gas, heat)
  • Time series, such as measured values from generators or consumers
  • 3D building data, such as LOD2 data

By combining expertise in the fields of energy and IT, the Fraunhofer Center Digital Energy offers services that include upstream and downstream processes in addition to the visualization of this data. Upstream processes include, for example, the validation of data sets and the elimination of data errors. In addition, in many areas, such as network data, different data standards or proprietary solutions are used. Therefore, it is part of our services to process and visualize different data formats in order to ensure maximum compatibility with preexisting data. Downstream processes include the interpretation of data and the derivation of recommendations for action.

Data preparation and interpretation

  • Data validation and elimination of errors
  • Enrichment of data with publicly available data sets
  • Processing and preparation of various data formats
  • Derivation of recommendations for action

Visualization

  • Comprehensible representation of complex interrelationships with application-specific graphics and tools
  • Consideration of the temporal and spatial dimension incl. georeferencing on maps
  • Interactive elements (e.g. manual filtering or arranging of data)
  • DSGVO compliance (aggregation of personal data)