The overall objective of the project is to develop AGI (Artificial Grid Intelligence) to become an alarming protection system that can warn of potential high-resistance earth faults and manage via sectioning to identify which sections have high-resistance earth faults.

1. Detect high-resistance faults and report this type of event to the network control center
2. Develop effective methods to quickly find this type of fault situation.

• • Receive notification of a high-resistance earth fault in the distribution network in scada.
  • Be able to section up to the fault location.
  • Assess whether a drone with a heat-seeking camera can be sent up to uncover the fault location.

Glitre Nett has challenged Siemens to try to create a protection system that is able to detect high-resistance faults in the network.

• Measuring equipment for detecting high-resistance earth faults
• Machine learning algorithms for the identification of ground faults
• Data platform for collection and analysis

Siemens' development team in Erlangen, Germany also sees the need and they want to have this tested and finally implemented in their new venture within artificial intelligence, which is a new way of detecting faults in the power system.

Siemens also sees that this is a challenge in many countries (USA, California, Australia) where power lines have started large forest fires that can lead to catastrophic destruction.

Glitre Nett has gained insight into the fact that Siemens is rethinking protection systems in the power system and has long worked with AI (artificial intelligence) for protection systems.

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• , Glitre Nett