Decentralized Energy Trading Infrastructure and Industrial + Residential Energy Agents

Practical example and current challenges

  • Centralized energy marketplaces must look at balancing energy demand and supply on the overall grid level. Given the required complexity of calculating, an optimum of such a solution for the whole grid and each and every participant is nearly impossible.
  • The energy-saving potential of local and residential loads is not fully harnessed at the grid level, because the calculations are would be too complex and would lead to breaching data privacy, because of a need to get behavioral data, etc.
  • Decentralized (i.e. not centrally operated) energy trading marketplaces, allow more accurate trading of energy supply and demand, thus requiring only a small loss of energy through long distance transportation over multiple levels.
  • Smaller unit of energy supply and demand (e.g. residential unit, electric vehicle) can participate in energy exchange without the need of aggregation services (e.g. virtual power plant, demand side response).
  • All kinds of residential and mobile units consuming or producing electricity can become users of the system. Energy saving can be achieved on the lowest grid level. Optimizing grid usage presents a more efficient way to achieve energy saving in comparison to expanding existing grid capacities.
  • By applying a decentral managed and operated technology stack and privacy-by-design ap-proach, individual data can be used security without exposing it to any data crawler.
Decentralized Energy Trading Infrastructure and Industrial + Residential Energy Agents

What added value does the "GAIA-X project" offer?

  • GAIA-X guarantees the secure exchange of data between the Secure-Multiparty-Computing (SMPC) nodes and the transmission of the protocol calculations between the nodes.
  • GAIA-X ensures that smaller units of energy supply and demand (e.g. residential unit, electric vehicle) can participate in the energy exchange without the need for aggregation services (e.g. virtual power plant, demand-side reaction).

Use Case Team

  • Christian Heise - Robert Bosch GmbH
  • Jared Weinfurtner – Robert Bosch GmbH
  • Lars Wegner – Robert Bosch GmbH
  • Jan-David Stütz – Robert Bosch GmbH