How power companies can use data for smarter operations

Many Norwegian power companies are now exploring how artificial intelligence (AI) can be used to streamline energy management, grid operations, and production. However, the benefits depend on both data access and data quality. The core challenge is how to go from huge amounts of data to concrete and measurable business value?

Over the recent years, the power industry has undergone a major transformation. Complexity has increased significantly, with 15-minute markets, more distributed generation, greater variation in consumption, higher peak loads, and an increasing share of weather-dependent, renewable energy. Where it used to be sufficient for many companies to plan grid operations and production on a day-to-day basis, today continuous (near) real-time optimization of both grid and production is required to protect margins and ensure security of supply.

For the power industry to succeed in an increasingly complex energy system, data must be treated as a strategic asset.

Data is no longer a byproduct of day-to-day operations. Companies that are able to leverage real-time operational data into insights and concrete actions gain clear competitive advantages: lower operating costs, higher utilization of production capacity, and better ability to operate in a complex power system without compromising on security of supply.

Many Norwegian power companies are exploring how to utilize AI to streamline energy management, grid operations, and production. But the results depend on data access and data quality. The challenge is: How do you go from having huge amounts of data to harvesting great value from it?

From raw data to smarter operations with AI

Data is the very foundation of a modern and robust power system. Power companies that are able to collect, quality assure, and share real-time data lay the foundation for more efficient, reliable, and sustainable solutions. This is consistent with the EU's assessment of digitalization and data sharing as key drivers for a resilient energy system.

Hence, the question is no longer whether data can create value, but how raw data can be transformed into smarter operations. Success requires structured data management and high data quality. The saying "shit in - shit out" still applies - bad data gives bad answers. The introduction of artificial intelligence (AI) makes the requirements for data management and data quality even more stringent.

The business value of AI is directly dependent on access to structured and reliable data. Power companies that are able to turn raw data into operational and decision-supporting insights gain a clear competitive advantage. They can predict, optimize, and automate both production and grid operations faster and more accurately than their competitors. Unsuccessful companies, on the other hand, remain reliant on manual processes, personal spreadsheets, delayed information, and fragmented data sets - all of which increase risk, reduce efficiency, and drive both operational and investment costs.

With high data quality and the right application of AI, utilities can achieve smarter operations, lower costs, and better utilization of existing capacity.

Read how one of our customers saves SEK 465,000 per month by cleaning up data >

Some key areas where AI is already contributing to better balance and smarter operations in the power system are:

• Production forecasting: AI analyzes historical and real-time data to predict production and consumption patterns, optimize resource allocation, and contribute to more efficient market balancing.
• Smart grids: AI can strengthen grid operations by combining real-time operational and weather data with wind and solar power forecasts. This gives grid operators better insight into the state of the grid and a more robust decision-making basis for planned connections, congestion management, and handling of potential operational deviations.
• Predictive maintenance: AI models, including deep learning, are used to predict equipment failures with high precision. Research published in the International Journal of Science and Research shows that this can reduce unplanned downtime by around 35% and increase energy production in renewable systems by around 8.5%.
• Battery management: In the future, AI will play a key role in optimizing the charging and use of battery capacity, both in electric vehicles and other energy storage systems. This contributes to better utilization of flexibility, reduces peak loads, and further stabilizes the power system.

Data - the foundation for more renewable power

Succeeding with data-driven operations in the power industry is about understanding how the power system actually works - the interaction between production, grid, market, and regulatory framework. In order for data to become a real foundation for more efficient production and distribution of power, deep industry knowledge must be combined with solid technology expertise.

Power companies today are sitting on vast amounts of data from AMS, SCADA, IoT sensors, weather models, and market platforms, but many are still struggling to extract operational value. The real challenge is to understand the data, the connections between them, and how they can be used to make better and safer decisions. This is demanding in a sector where small mistakes can have big consequences and where real-time decisions must be made without compromising the security of supply.

It is precisely at the intersection of technology and industry expertise that Cegal delivers solutions with high business value. Cegal has worked closely with power companies for decades. We know the industry, the processes, the regulatory requirements, and the operational challenges. This industry understanding, combined with deep technology expertise in data, data analytics, cloud platforms, and artificial intelligence, enables us to help utilities move from complex and fragmented IT environments to integrated, digital solutions that create demonstrable results.

When data is treated as a strategic asset, utilities can operate more efficiently, more profitably, and more sustainably - making better use of existing infrastructure and increasing the share of renewable energy in the system. Data can then become a robust foundation for more renewable power.