Artificial Intelligence (AI)

In nowadays life, Artificial Intelligence (AI) plays a significant role in Social Media and Streaming providers already, such as Instagram and Netflix. The AI can be used to place personalized advertisements due to the shared data of its user’s. Nonetheless, the AI approach can be implemented in fast swathes of TSO’s core business to adapt large amount of data providing support for decision making, either from a System Operation perspective or within Corporate Development and Business Administration.

The AI approach is part of computer science that focuses on simulation of human intelligence applied via machines and computer systems. One aspect of AI is the machine learning (ML) which is able to recognize a certain pattern (e.g. of a picture) in such a way, to memorize and identify similar pattern. A more advanced aspect of ML is the Deep Learning Method (DL). A common approach to realize such DL is to build a so-called Artificial Neuronal Network, which was inspired by the human brain. The main idea is that such an algorithm can process information out of a variety of input data to “learn” a specific task’s fulfilment.

Moreover, it can be distinguished between a strong AI, which is equal in the capability of a human mind and can be applied to variety of areas, and a weak AI, which is just capable to fulfil a specific task of a certain area.

All the existing AI implementations must be considered a weak AI.

Technology Types


Components & enablers

Up until now, the company that provides services within the new Platform Economy own their AI algorithm. Therefore, the software code is operated on locally redundant Data Centres.

Advantages & field of application

In general, AI software solutions show high potential in improving an organization’s performance and can be implemented in both – technical and economic terms. The main advantages and useful applications in TSO’s core business is still under discussion, but might be established in one of the following:

  • Using deep learning methods in Drones for maintaining purposes of overhead lines.
  • Applying Digital Twins of high-voltage equipment of high importance.
  • Introducing software in controlling & accounting to improve administration performance within an organisation.
  • Using optimization code for automated energy trading.

To use those affects, a proof of certain advantages need to be done by TSO’s. It is necessary to identify specific potential in either grid operation, market design or administration processes to accelerate the development of AI software solutions and to lead it into “best practice” examples.

Technology Readiness Level

TRL Score 6 – technology demonstration.

Research & Development

For the time being, there are many methods and concepts developed for different machine learning purposes. A key to a useful implementation of AI software solutions in TSO’s core business is to launch external and internal projects to adapt those measures to experience best practices and lessons learned.

Best practice performance

Up until now, there is no decent “best practice” example from a TSO’s perspective.

Best practice application