Predicting power market imbalances with AI

In the Nordic power market, maintaining equilibrium between electricity production and consumption is critical—and challenging. For one of Norway’s largest power companies, navigating the balance market meant making high-stakes decisions in real-time. Together, we built an AI-powered platform that combines machine learning with physical flow models to simulate the market and support traders in staying ahead.

Challenge: In Norway, electricity is traded in two ways. Financial trading of future contracts and derivatives takes place on Euronext, while Nord Pool has the balance market. The purpose of the balance market is to ensure a balance between power production and electricity consumption.

In the Norwegian power system, which is part of the Nordic and European power market, production and consumption of electricity must be in balance at all times. Electricity cannot be stored on a large scale; therefore, imbalances between production and consumption must be addressed immediately. The power system is continuously monitored to ensure that reserves are available to adjust imbalances in real-time.

This balancing market comprises various types of reserves that are activated over different time scales, which can be activated automatically or manually, depending on the urgency of the imbalance. The players in the market, typically power producers and large consumers that may have flexible consumption, offer capacity in these markets, and are compensated for making this available. For companies involved in power production, trading, or managing industrial loads, the balance market presents both opportunities and risks, where precise forecasts and automated decision-making systems can provide significant benefits.

When imbalances occur in the system, for example, when consumption suddenly exceeds production, traders can offer up-regulation, i.e., increased production or reduced consumption, to contribute to balance. Similarly, if there is too much power in the system, they can offer down-regulation by reducing production or increasing consumption. Correct timing and a precise understanding of the market mechanisms are essential to ensure profitability and stability in the power system.

Solution: We developed an advanced decision support platform for the balance market that combines machine learning with physical flow models – what we call a digital twin of the power system. The model has been developed in close collaboration with the traders and should be a valuable tool for them, not a replacement. By avoiding overtraining and ensuring understandable predictions, we have developed a solution that enables people and machines to work together effectively.
The model is composed of several machine learning models that together simulate the power system, of which the Nordic market is a part. The models are designed to be a valuable partner for traders who closely follow this market.

Result: The platform is under continuous development and provides the traders with an essential tool in their toolbox. The first version of the model is designed to provide traders with useful information and better insight than their competitors. It is in the plans that the platform should be able to make independent trading decisions when there are no traders at work. This not only requires a strong focus on delivering perfect predictions, but also a strong focus on risk management and handling.

By being correctly positioned in this market, the customer can generate significant revenue, or, just as importantly, avoid incurring substantial losses by not being able to deliver registered power. 

Antire has completed several hundred AI and machine learning projects

Antire has completed several hundred AI and machine learning projects for our customers. What the projects have in common is that they can be developed and implemented in a short time, while providing outstanding value to customers. Here you can read about four of the projects.

Antire has been working with machine learning and artificial intelligence (AI) since 2013. Over the years, we have completed several hundred projects across various industries and with some of the leading enterprises in the Nordic region. 

What most of the projects have in common is that they involve few people and take a short time. It usually takes 1–2 months from start to implementation and production. The projects typically last no more than six months. The AI solutions solve specific tasks, providing excellent value and paying off quickly. 

Machine learning and AI have followed Moore's Law in terms of development, with capacity doubling approximately every 18 months. In the last couple of years, however, growth has accelerated, with capacity doubling every 3–4 months. This means that the AI ​​solutions we deliver do more and have greater value for customers.

The projects can be made available in several ways, for example, as independent apps, dashboards, and solutions that are integrated into the customers' ERP systems. The value depends on use. It is therefore essential that they have a good interface and are easily accessible to everyone who will use them. If customers wish, they can add their factors afterwards. 

 If you’re exploring how AI and machine learning can support your business, we’d love to hear from you.

Get in contact with Øyvind Spørck—our Head of Tailored AI and a leading expert in applied machine learning.