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Big Data and Analytics for Operational Efficiency: Exclusive Interview with Peter Soderstrom of Vattenfall Distribution

Peter Soderstrom

Vattenfall Distribution is one of Sweden's largest and most prominent distribution system operators. Because of that, the company often leads the way when it comes to finding ways to increase operational efficiency, harness the emerging digitalization trends, and embrace big data. 

These are the topics that Peter Soderstrom of Vatenfall will cover in his present at this month's SGTech conference, when he gives a talk called "Big Data and Analytics for Operational Efficiency: Leveraging big data from across the grid and driving real time analytics to make systems more predictive and responsive and optimise network functionality and efficiency." Peter was excited to speak with Energy Central about these topics and give a preview about what he's excited to share at the conference later this month.

Note: Two other SGTech speakers have also shared previews of their presentation with Energy Central: Armando Temporal of CHESF and Anjos Nijk of ENCS.


Matt Chester: Hi Peter, and thank you so much for taking time out of your busy schedule to share a bit about this topic with me. To begin, can you please give an overview of Vattenfall Distribution and specifically what your role is?

Peter Soderstrom: Vattenfall Distribution Sweden is one of the largest Swedish DSOs operating the distribution and sub-transmission grid in the mid and northern part of Sweden. In the company, I am the head of digitalization hub with the responsibility to innovate our business with the primary focus on digitalization and flexibility.

MC: Your presentation at SGTech is on Big Data and Analytics for Operational Efficiency-- can you talk briefly about why this topic is an important one?

PS: The energy system turn-around is not only about building sustainable energy generation, but also how we can reach an efficient system that meets the requirements in society. With the technology developments done in all areas, much improvement can be seen, however using vast amounts of information that's potentially available is still a challenge for most DSOs. It is not enough to analyze the information-- it is when you put the analyzed information to work in the processes the real gains are realized. I will, in my presentation, give a number of examples of how this can be done.

Image result for DSOs

MC: What sort of tools are you seeing emerging in the data-driven DSO model that were not there even just a few years ago? How do you see that changing and evolving even more in the coming years?

PS: The development of AI, with all its sub-areas, the computing power made available through either cloud computing or dedicated solutions, and tools/methods to integrate data easily in for example "data lakes" are all key enablers to lower the hurdles to making the DSO more data-driven.

For the near future, we will see a large set of new flexibility services made available through the insights gained by big data and analytics to solve the energy system challenges. There is, however, also increasing challenges with IT security and information security that needs to be solved to reach a robust energy system.

MC: How does the emerging trend of digital monitoring across the grid change the business model of utilities? And how does it affect the end-consumer?

PS: The most significant gain is the development of more standardized and predictable flexibility services. Both these aspects will enable utilities to start using these services and thus the business model implicitly changes from only building new network to handle all new requirements to a more diverse mix.

For the end consumer, there really is two sides to this. Some services will be made available completely transparent for the user and others will require the customer to take an active role in regard to their energy use.

MC: An interesting topic you're going to cover at SGTech is Dynamic Line Rating-- can you give a brief overview on what this concept is about and where you see it going?

PS: DLR is about using real-time information about both the network status and the surrounding weather conditions. An overhead line is typically statically rated, however if the wind just moderately is increased over the assumption made for the static rating the capacity can drastically be increased for almost no cost. If the line is in the same area as much wind power then the symbioses are perfect, but the solution can basically be used in most cases. 

Image result for dynamic line rating

MC: Outside of your presentation, are there any topics that you're excited to learn about at the upcoming conference?

PS: The use of AI in all its parts is fascinating as well as the developments around the digital substation. 

MC: To end, is there anything else you'd like to share with Energy Central readers before we go?

PS: What is really interesting as a continuation of big data, analytics, and AI is the steps taken towards the "digital twin." This could really be the tool to take the next step to make the DSO business not only efficient, but optimized. 

 

 

Interviewer's Note: Peter will be discussing these issues and more during his presentation at SGTech Europe 2019, taking place in Amsterdam from March 26 to March 28. As mentioned, this presentation is titled "Big Data and Analytics for Operational Efficiency: Leveraging big data from across the grid and driving real time analytics to make systems more predictive and responsive and optimise network functionality and efficiency."

To see more information about and to register for the SGTech conference being put on by Smart Grid Forums, click here

Matt Chester's picture

Thank Matt for the Post!

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