All posts
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How We Made Accurate Power Consumption Forecasts in Just Six Hours
The Data Science section competed to make the best forecast in 6 hours. Read more
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Flow based market coupling from a data science trainee standpoint
Flow based in my trainee rotations I started in Statnett in 2021 and spent the first year-and-a-half as a trainee. Although I have worked in three very distinct departments in Statnett as part of the trainee-program, I have noticed a somewhat common thread throughout my traineeship. This common thread is a mysterious concept known as… Read more
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The green transition: Why the availability of power system data matters
The green transition has overwhelmed the power grid connection process for new customers. Swift and cost-effective connection relies on the expertise of power system analysts. To achieve this, Statnett believe we must enable analysts to adopt a data-driven approach akin to data scientists. The biggest challenge is just the sheer volume of projects. There are only… Read more
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Cimsparql: Loading power system data into pandas dataframes in Python
In 2019, we started working on a model that should be able to handle intra-zonal constraints in the upcoming balancing market. That methodology has been presented in a previous post in January 2022. In this post, we will focus on an open source Python library called cimsparql that we have developed to support this model.… Read more

