Finding the best sites for hydrogen and wind production—with AI

Identifying the best locations for hydrogen plants or wind farms requires navigating an overwhelming number of variables—from land use and regulations to energy prices and local sentiment. For one of Norway’s largest energy companies, this process was time-consuming and often inefficient. Together, we built an AI-powered tool that analyzes over 100 factors to instantly pinpoint ideal sites—enabling faster, smarter, and more productive conversations with stakeholders.

Challenge: Hydrogen production will be a crucial component in the future energy mix because it efficiently stores energy and can be produced with surplus power. Hydrogen production is most efficient when it occurs close to both power sources and consumers. At the same time, several key considerations must be taken into account when setting up a hydrogen factory, including electricity prices, location, regulations, logistics, emission possibilities, and local interests. Finding the best locations requires analyzing vast amounts of data. Typically, this task is performed manually. Those who do the work spend hours scrolling through map services, hundreds of hours reviewing various documentation, and attend numerous meetings each year with both landowners and municipalities. Most of them to no avail. 

Solution: We developed a tool that analyzes over 100 factors to identify optimal locations for hydrogen production, down to areas as small as 10 x 10 meters. Users can weigh factors, enter requirements, and make adjustments in real-time in dialogue with stakeholders. The tool quickly ranks areas according to their suitability, considering both proximity to potential customers and investment factors, as well as finances. 

The tool can also be used in meetings with stakeholders, whether they are municipalities or landowners, to quickly identify areas to focus on. 

Result: The efficiency of the work with location assessment has increased by almost 90%. What used to take days manually clicking in map tools is now done in minutes. Our customer, one of Norway's largest power companies, also has a department dedicated to wind power production. When this department saw the tool the hydrogen gang had obtained, they wanted a similar solution. Thus, we also developed a model that calculates the expected annual electricity production for wind turbines of different sizes, as well as the expected development costs. Perhaps even more importantly, you can quickly identify areas that are not suitable, and can thus focus all efforts on the best places for wind power production.

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. 

We present four concrete AI and machine learning projects that we have recently developed and implemented:

• Predicting power market imbalances with AI.
• Halving power consumption in mobile towers with AI.
• Keep the fraudsters out - AI that stops SMS fraud in real time.

 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.