11 AI & Energy Initiatives in the Nordics
Artificial Intelligence Applied in Relation to Energy
This article is co-written together with Christoffer Bouwer who recently finished his MsC in Industrial Economics Technology (SIVING) at the Norwegian University of Life Sciences. His specializations are within innovation, management, mechanical engineering and energy systems. He has worked with innovation processes and led conferences within the energy sector.
Using machine learning techniques for a variety of applications has grown more popular with established companies in the Nordics and it has also led to the creation of new companies specialising in the use of artificial intelligence within the energy sector or has managed to cut emissions due to their AI initiatives. The list made here is not comprehensive and will be diverse, as such it must be read at face value. This is meant to spark a discussion and it would be great to find more companies operating within this space or expanding on initiatives that could be great applications for assisting in the process of providing energy or reducing the cost of maintaining infrastructure related to energy. Hardware solutions connected to AI or a combination of sensors and AI is equally a good combination to consider — not only purely software-based solutions.
1. Aker BioMarine
Aker BioMarine reduced energy use through analysis of crustacean populations used artificial intelligence (advanced analytics and prediction). Through using machine learning Aker BioMarine wants be able to predict the spawn of small crustaceans much better than they do today, this will make their operations more efficient, reduce the use of fuel and reduce CO2-emissions from their entire fleet. The model can also be used for research, and in this way gain new knowledge. They are indirectly increasing their climate friendliness by using AI internally in their company to limit the time they spend to search for fish with fuel-guzzling boats. They did this together with Amesto Nextbridge. Crustacean make up a large part of the earth’s biomass. The gathering of crustaceans in the sea can be so vast that they can be seen from outer space, however the sea is large and understanding the changes in the population is important — and can be assisted through machine learning.
2. Elvia (Norway)
To develop and operate the electricity grid in an efficient and future-oriented manner, Elvia is focusing on developing competencies within data science and machine learning. Data about the electricity grid is gathered from operation, maintenance and system-faults within the grid on a large scale and gives possibilities for use of this data. The company will produce nearly 5 billion KwH renewable energy, and is amongst the largest district heating and grid companies in Norway, the third largest that delivers electricity, and the sixth biggest fiber provider in Norway.
3. E-Smart Systems (Norway)
Their company attempts to reinvent energy systems through their predictive maintenance and Connected Drone using industrial grade deep learning to turn visual inspection data into actionable asset insight. Together with this they have a Connected Grid solution that works as an intelligent top system that provides decision support for optimal operation, maintenance and planning of grids. Not only do they do this on a delivery level however they are thinking about how to make it easier for the consumer to get an overview over energy consumption in what they call a Connected Prosumer providing real-time visualization of energy consumption detailed to the preferences of the consumer, as well as any of the energy production on site.
ESmart Systems vant prestisjekontrakt med kunstig intelligens i USA
Halden-baserte eSmart Systems kan ha skutt en amerikansk gullfugl. Selskapet leverer kjerneteknologien til et system…
Hvorfor AI og maskinlæring er avgjørende for ditt nettselskaps framtid
Vi står overfor en datarevolusjon i nettdriften. AMS-infrastruktur, sensorer i strømnettet, værdata og data fra sosiale…
4. Leanheat (Finland)
Artificial intelligence learns to heat energy-efficiently. This is done by installing climate sensors in apartments. With the operations they can both help with heating in an optimal way and potentially building maintenance given the right data. They claim to lower energy costs by avoiding power peaks, capacity can be used in a better way. Leanheat aruges that they can reduce the maximum power usage by 10–30%. Their experience from Finland shows that a 20% cut in the peak power requirement typically means 3–10% savings in addition to savings in energy consumption. Their artificial intelligence learns the domestic consumption profile of hot domestic water and adjusts the heating to charge and discharge energy accordingly. This balances the building’s power usage and also contributes to a greener world.
5. Meshcrafts (Norway)
MeshCrafts deliver e-mobility with a focus on everything smart — smart cities, smart grids and smart transport. Their main offering is a Software as a Service — platform SmartCharge that is an open marketplace for the charging of electric vehicles. Their main office is at the Oslo Science Park. The way machine learning techniques is used for MeshCrafts in the analysis of data on their platform.
6. NCE Smart Energy Markets (Norway)
A cluster formed by several Norwegian energy is addressing the usage of AI in energy markets and thereby indirectly climate change. They have established several working groups that have identified different issues to be raised and addressed. One of their main concerns is the current best practice of using technology within health, smart buildings and the platform economy. Another important issue they are exploring is the optimal relationship between technologies within smart buildings and health. A central concern for the working group lies within implementation — as such ‘core business’ while considering on the other hand the possibility of outliers going beyond the established company current operations or office. Strategy is oriented towards a cultural change and a new mindset as much as it is about the integration of shared platforms across business areas.
7. Otovo (Norway)
Through their mapping and satellite imagery Otovo collects all the necessary information from the customer (roof images, fuse box, type of roof, preferred place of installation of the inverter etc) They guide the customer through the process, while taking into account their preferences. On top of that, they can follow the installation process on their customer page or via their App. They are the largest company in terms of installing units in Norway and Sweden. As such they have delivered more than 3 000 units in Norway and Sweden. That makes them into one of the leading companies on delivery of a comprehensive solution for solar roof for private and business customers. In 2018 Otovo acquired Sunmapper’s Photovoltaic Irradiation and Surface Calculation software — Sunmapper PISC — including IP transfer with perpetual and universal usage rights, for an undisclosed amount. The technology enables Otovo to ingest 3D surface point clouds generated with laser imaging (LiDAR), satellite imagery and stereographic reconstructed models, returning solar irradiation and individual roof surfaces for PV planning.
8. Skyqraft (Sweden)
Skyqraft, a Swedish startup using AI and drones for electricity power-line inspection, has picked up $505,000 in early backing. Founded in March 2019 and launched that September, Skyqraft provides what it calls “smart” infrastructure inspections for power-lines. One of their investors is Antler, with participation from a number of angels, including Claes Ekström and Tomas Kåberger.
“Our competitors are mainly quadcopter drone operators, and they inspect only the transmission grids. We on the other hand, offer our customers a full service and inspect both transmission and distribution grids also using our machine learning system to detect any threats automatically.” Sakina Turabali, TechCrunch the 13th of January 2020.
9. Sevendof (Norway)
Sevendof is a technology startup developing a scalable drone service platform, enabling businesses to use drones without ownership or operation. They are developing a platform that offers drones as a complete service, without requiring ownership, training, or presence in the field from the end user. Our platform consists of a network of stations and long-range drones with built-in autonomy. Each mission defined by the user is fulfilled automatically, providing high-quality data to the end user through the cloud. They are mainly piloting their solution with energy companies, yet their technology could have a larger area of application.
10. Stavanger county (Norway)
Together with several other European Cities, the Norwegian City of Stavanger has gotten 60 million NOK in EU financing for the project AI4Cities through the Horizon2020 initiative. Ambitious plans have been laid out by these cities to improve the usage of AI for pre-commercial evaluation of purchases. Most cities within this project are Nordic capitals like Tallinn, Helsinki and Copenhagen, but also Amsterdam, which is interesting due to the fact that Stavanger is not, and it goes to show that the Norwegian combined efforts for AI and climate are quite decentralized at the moment, if even initiated at large scale at all.
Stavanger vinner H2020 prosjekt - førkommersiell anskaffelse, AI & klima
Stavanger kommune har sammen med blant andre Amsterdam, København, Tallinn, Helsinki og ICLEI, fått tilslag på…
11. Tomorrow (Denmark)
Tomorrow claims to be building tech that empowers people and organisations to understand and reduce their carbon footprint. They attempt the user to understand the climate impact of every choice they make. This company has a stylish brand and attempts to appeal with its tool meant to empower the user to make better decisions. Their statement is that climate impact is about information, and modern technologies are the tools required to turn complex data into intuitive and actionable insights. They see data as the catalyst to large-scale behavioral change.
Nordic businesses and organisations are organising to learn more about AI with regards to both climate and energy, addressing the case of how to solve the issues we are likely to face in the coming period of time. The list we have provided shows an overview of some initiatives at the forefront of the Nordic AI community, while there are also others we have not covered. Large public companies and utilities like Telenor, Statsbygg and Statkraft in Norway are working to increase their AI competency as well, becoming increasingly better equipped over time. With our background from Norway we had far more Norwegian companies represented in the current list, yet we will strive to provide a broader Nordic focus — hopefully, the list will continue to grow as we enter an increasingly digital age. Perhaps you can suggest a company?
This is #500daysofAI and you are reading article 281. I am writing one new article about or related to artificial intelligence every day for 500 days. My current focus for 100 days 200–300 is national and international strategies for artificial intelligence. I have decided to spend the last 25 days of my AI strategy writing to focus on the climate crisis.