Design of a management infrastructure for smart grid pilot data processing and analysis

Future smart grids will combine power grid technologies with information and communication technologies to enable a more efficient, reliable and sustainable energy production and distribution. To realize such a smart grid, large scale pilot projects are currently implemented and evaluated. Such pilot projects generate an excessive amount of data that needs to be processed: energy measurements, information on available flexibility from smart devices that can be shifted in time, control signals, dynamic prices, environmental data, etc. To validate and analyze the gathered data and adjust the running experiments in real-time, an optimized data management infrastructure is needed as well as comprehensive visualization tools. In this paper we present a data management infrastructure optimized for the follow up of the large scale smart grid project called Linear. In this project a pilot in over 200 households is implemented to evaluate several business cases including the balancing of renewable energy supply and the mitigation of voltage and power issues in distribution grids. By decoupling the gathering of the incoming data, the processing and storage of the data, and the data visualization and analysis on different servers, each with their own, optimized database, we obtain an efficient system for validation of the generated data in the pilot, management of the deployed set-ups and follow-up of the ongoing experiments in real-time.