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Linc’s AI-Powered Digital Twins for Proactive Capacity Maximization and Maintenance Optimization

In the ever-evolving landscape of energy infrastructure, Linc emerges as a trailblazer, harnessing the power of artificial intelligence to transform the management of distribution transformers.

Discover how the StairwAI second open call programme is helping them.

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Business Category
Energy

  1. Please introduce your company in one sentence.
    Linc develops IoT hardware to monitor buildings and grid networks.
  2. Kindly provide a one-paragraph description of your project.
    Linc is training AI models on data from distribution transformers to maximise capacity, increase life span, and optimise maintenance operations. Our project will develop and implement digital twins at a 1-second, real time resolution. Our modeling aims to forecast possible failure conditions at least 5 hours in advance, allowing for corrective measures by the grid operator. The solution is designed for scalable, plug-and-play deployment on any make, model or size of medium-low voltage transformer.
  3. How is the StairwAI support program contributing to the development of your solution?
    Linc gathers high volumes of data for electrical, spectral and thermal conditions of distribution transformers. The StairwAI program is supporting development of advanced AI analytics to extract timely data insights based on this data. This creates value for our DSO clients, and business models for Linc.
  4. Could you outline the upcoming roadmap or plan for the next few months?
    Linc has partnered with Trefor, a leading Danish DSO, and deployed monitoring hardware at over 100 transformers. Data from these transformers will be used to develop grey box models and related AI algorithms for advanced analytics. This data engineering will be implemented in partnership with an AI Talents company. The project will end with a fully-functional user interface with transformer analytics for Trefor, and will serve as a case study for commercial expansion.

Let’s see how the implementation of AI can improve their solution!