Blockchain-based decentralized energy market design and management structures


Blockchain technology offers an excellent opportunity to trade electricity within the scope of the energy transformation. Using this technology as a foundation, the Best research project is developing new forms of commercial energy trading, a blockchain-based decentralized energy market design and management structures.

Project description

Over the course of the energy transformation, the increased reliance on volatile power sources and growth of decentralized renewable energy systems is creating new challenges in the utilization and efficient distribution of power in grid regions that to date have been geared toward conventional energy systems.

fortiss and its project partners are aiming to develop a power exchange platform on the basis of an electricity market trading system (EMTS) that can be used to more efficiently distribute and trade electricity in a way that is conducive to the grid. By using blockchain technology, the EMTS provides a secure and efficient marketplace for consolidating the supply and demand of electricity while simultaneously making information, such as certificates of origin, available in a transparent manner. All of this will take place independent of the type (consumer, generator, storage) and classification (household, industry). The goal is to establish a real-time market that will make it possible to derive new high-frequency products and satisfy the requirements of the energy transformation, the latter which is marked not only by volatile sources of renewable energy, but fluctuating consumption, such as through electromobility.

Project contribution

fortiss is developing multiple correlated subsystems for the EMTS. One area involves improved forecasting, which plays a very important role for both electricity consumption and user behavior in terms of the optimal planning and operational management of resources. For this reason, in order to plan electricity consumption for a future period of time, the system should make this determination based on a defined time span. With this in mind, a prognosis model of the future load profile, which predicts consumption for electricity demand and planning, will be developed based on the time span analysis and with the use of machine learning technology.

fortiss is also developing a pooling platform that guarantees participating users informational self-determination, in particular by taking into account their personal rights and protection of the private sphere. This occurs first and foremost through the generation of highly-personalized electricity usage profiles created within the framework of the analyses that are carried out. 

To increase acceptance of the system among users, fortiss is relying on this interactive and collaborative platform to examine how user profiles can be automatically derived from consumer behavior patterns. The system would then recommend bidding strategies to users for balancing the residual electricity and achieving electricity savings. Furthermore, the system will be used to evaluate and improve a user interaction concept so that it results in benefits in terms of convenience and promotes an understanding of the processes in the power grid.

To assess the practicality and user acceptance of the concept, the fortiss laboratory environment will be connected to the EMTS and the pooling platform. Where possible, this will also involve integrating the central management system and other developments from the project partners into the laboratory environment. Furthermore, other participants will be emulated with the help of a co-simulation environment in order to test the functionality and scalability. With this background and the knowledge gained from the research, fortiss will then support the customer testing activities.

Project duration

01.01.2021 - 31.12.2023

Dr. Yuanting Liu

Your contact

Dr. Yuanting Liu

+49 89 3603522 427

Project partner

Reiner Lemoine InstitutFraunhofer FOKUSEnergieforen Leipzig GmbHe-regio GmbHHochschule WeserberglandOLI Systems GmbH