dLab launches dInsight, visualizing the status of the distribution grid

The Smart-grid company dLab, one of EU top 40 high-tech start ups according to High-Tech Venture Days, launches dInsight. A graphical decision support system that shows the status of the grid and is a platform that helps electrical utilities to reduce power outages and costs. dInsight , based on visualization of big data, enables prioritization of investments and maintenance efforts. Proactive action can be taken preventing electrical outages and as a result costs are reduced

dLab has developed a patented algorithm that analyses and categorizes all incidents in the power grid. The results will help the electrical distribution company to identify fault before leading to an outage and greatly reduce troubleshooting time by indicating where the faults are located and the fault characteristics.

• dInsight has analyzed over 25 000 incidents in the Swedish power grid.
• In up to 78% of all faults an early warning of that fault is available.

dInsight gives the user an easy and accessible overview of the grid status and provides a basis to prioritize actions where they are most needed and effective.

"Digital solutions should help the electrical utilities to make the right decisions. We have developed dInsight to give our customers an overview of the status of the grid in order  to be able to prioritize maintenance tasks and investments. However it is also a great tool for fault investigations and faster corrective action" , says Mats Didriksson, CEO of dLab.

• In order to reduce electrical outages it is important that all different parts of the organisation has access to accurate and condition based decision support information. dInsight provides that from day 1.

"We see that now, for the first time, our customers have a graphical holistic overview of the grid condition. Where in the grid disturbances occur over time". dInsight is therefore useful as an overall decision support for senior management. Decisions about maintenance and grid investments can now be based on the actual condition of the grid". Mats Didriksson concludes.