TRANSMISSION & DISTRIBUTION TECHNOLOGY
T
hrough the research project KogniGrid, Kongsberg Digital has investigated how digital twins can be used to ensure optimal operation
of power grids. As a result, Kongsberg Digital recently launched a digital twin for power grids, called Kognitwin Grid. Power operator BKK Nett has now signed an agreement on a six-month R&D project to further develop and test Kognitwin Grid. Based on the company’s proprietary digital platform, Kognifai, Kongsberg Digital has developed the SaaS product, Kognitwin Grid, in close collaboration with industry and research partners. Tis is a digital twin of the power grid, which provides insights and forecasts to identify grid bottlenecks, simulate grid scenarios and optimise grid investments. Te focus has been to give operators the ability to foresee challenges to the grid infrastructure, automate alerts and complex processes, to ensure complete control and pave the way for the digitalised energy system of the future. “While an increasing part of the
world’s energy systems and the means of transport are becoming electric, the pressure is increasing on the power grid infrastructure, which is not built to handle the new complexity. One of the solutions is to keep building out grids for maximum capacity, resulting in more costly infrastructure and thus more expensive electricity for consumers. Digital twins enable precise and data-driven real-time insight so that operators can forecast specific needs, introduce measures to balance the network and prevent black- outs without building it out”, says Hege Skryseth, President of Kongsberg Digital and EVP Kongsberg.
COLLABORATION ENABLES THE GREEN SHIFT Kognitwin Grid is a direct result of the KogniGrid project, launched in 2018, as a collaboration with BKK Nett, Tensio (NTE Nett), Statnett, Microsoft and SINTEF. BKK Nett has now signed a new six-month research project for further development and testing of Kognitwin Grid.
“Te grid operators hold the key to solving the challenges on the power grid and thus contribute to the green shift. We are pleased that BKK Nett will continue the close collaboration with us through Kognitwin Grid so that we
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BKK Nett has embraced the use of digital twins to boost its grid operations DE DIGITALVELOPMENTS
Power firm is one step closer to enabling the green transition of energy systems
together can find solutions that enable increased electrification of the society,” says Skryseth. Project manager R&D in BKK Nett,
Eivind Flatlandsmo, says that they have learned a lot during the 3.5 years the project has been running. Tey are therefore looking forward to the further collaboration with Kongsberg Digital. “One of our strategic goals is to become more data-driven in the decision- making processes for development, management and operation of the power grid. Tis requires large amounts of data and information from various sources, which in turn requires new tools and methods to generate the insight we need. Fundamental to everything is data quality and information security, without this we cannot rely on the results produced or the software itself”, says Flatlandsmo. “We have acquired valuable knowledge and experience from the close cooperation
with the partners in the KogniGrid project over a period of 3.5 years. We now know more about what a digital twin is, the work required to create a twin of value, and the potential the twin enables. Te project has also given us a picture of our digital maturity level, the capacity for development and implementation of new solutions. Tis requires the two most important resources we have and always want more of: people and time. “We are proud to continue our collaboration with Kongsberg Digital. We want to contribute to the green shift that challenges today’s power grid. To solve this, we need help. We cannot solve all our challenges alone,” Flatlandsmo concludes. Kongsberg Digital has also recently
entered into a similar agreement with Tensio, which was also involved in the KogniGrid project. Te agreement with Tensio includes a six-month trial of Kognitwin Grid.
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