Due to the large number of spatially distributed generators, consumers and prosumers, the uncertainties, but also the optimisation possibilities for an economic and secure energy supply increase enormously.
It is no longer possible to manually carry out comprehensive control and reliable monitoring of system properties. The multitude of data streams from the individual energy grids, plants and markets that have been built up in recent years can only be meaningfully monitored, evaluated and integrated into innovative applications using intelligent data-driven methods. AI will play a decisive role here.
The AI service for the energy sector is aimed at:
- Operators of energy networks (electricity, heat, gas).
- Energy suppliers and electricity traders
- Planners, developers and operators of renewable energy plants
- Planners, developers and operators of decentralised, multimodal energy supply systems
- Developers and operators of energy management systems
- IT service providers and control system manufacturers
Areas of application in the energy industry:
- Challenges in the feed-in of renewable energies (e.g. wind or solar energy).
- Coupling of sectors (electricity, heat, transport)
- Intelligent management of controllable consumers
- Automated grid operation
Examples
of AI-driven applications in the energy sector that have been developed in the KISSKI consortium:
AI-InnovA
AI-InnovA: Stochastic optimisation of wind-flex systems for innovation call for tenders using reinforcement learning
Responsible consortium partner: Fraunhofer IEE
VemoSat
VemoSat: Satellite-based vegetation monitoring for energy infrastructures
Responsible consortium partner: Fraunhofer IEE
Power-to-X Atlas
Power-to-X Atlas: Map visualisation of Power-to-X potentials
Responsible consortium partner: Fraunhofer IEE
Quick-start guide
Get in touch with us
Feel free to contact us via the contact form or use our initial consultation.