All posts
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Increasing line capacity by 20% using data science
In 2019, Statnett installed its first sensors for dynamic line rating. Now, in 2023, we have finally reached the point where we can use these sensors to increase the capacity of power lines with up to 20%. This post will explain how data science has played an important role in making this possible. 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
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Julia: A powerful alternative to Python
or have a look at the Julia homepage. Once you’re up and running, the easiest way to install a package when you’re ina Julia session is to just start using it by typing using <package name>, asfor example in Of course, the second time these lines are run from the same session it runs instantaneously. Read more