Resilience and automation in energy industry processes

Challenges

• Fault-free, low-maintenance operation without high costs/no long downtimes of small to large energy systems - from households to utilities/distribution grid operators
• Multiple failure scenarios from HW/SW failure to cyberattacks.

Our solution and research

• Resilient, self-learning and automated energy management system based on modern software architecture and the use of a variety of AI methods from the fields of Big Data, reinforcement learning and transfer learning, among others 
• Use of resilient methods to avoid downtime 
• Use of distributed, asynchronous communication methods to avoid information loss and faulty power management functions 
• Use of self-learning and -adaptive methods and process chains for automatic and autonomous adaptation to changing situations with simultaneous auditability through Explainable AI / Explainable AI and the possibility to manually influence the processes and process chains at any time 
• Use of state-of-the-art encryption methods for the methods of the EMS as well as for the communication between the methods and between the clients of the EMS.