AI for the energy sector
From prediction to acceleration, data-driven steering for a sustainable energy system. The energy transition requires more than ambition, it requires precision, speed and reliability.
The challenge for the energy sector
Energy companies, grid operators and producers face the challenge of continuously balancing supply and demand, strengthening infrastructure while ensuring affordability and sustainability.
How we are helping the energy sector
From predictive maintenance and grid balancing to customer insights and scenario planning, organizations that work smartly with data are building the energy system of tomorrow, reliable, scalable and future-proof.
At Data Science Lab, we help the energy sector deploy data & AI strategically and responsibly. Not as an experiment, but as a tool to accelerate efficiency, resilience and sustainability.
Why and what is the value?
The industry runs on data. Every cable, turbine, battery and customer contact moment generates information that is worth its weight in gold, if put to good use.
Data and AI make the difference
– AI predicts failures before they occur.
– Models simulate the impact of policy choices and weather conditions.
– Smart algorithms distribute scarce capacity fairly and efficiently.
And this is only a small sample. Want to know more? Schedule a free introductory meeting below.
What is the value of data?
AI directly delivers tangible value in the energy sector, both operationally and strategically.
1. Predictive maintenance
With AI, we predict the failure probability of critical components, such as transformers or cables. This allows maintenance teams to take preventive action instead of waiting out failures. This results in 20-40% fewer failures and increases network reliability.
Source: McKinsey via NumberAnalytics (2024)
2. Grid balancing
AI models predict peak load and help balance supply and demand in real time. As a result, grid operators are improving their operational reliability and reducing the cost of emergency measures.
Source: NL AIC – AI as an Accelerator for the Energy Transition (2023)
3. Price and demand management
By analyzing consumption patterns and market dynamics, we support energy companies in smart price and demand management. This results in better margins and higher customer satisfaction.
Source: Kickstart AI – How AI is Reshaping the Energy Sector (2024)
4. Energy planning and scenarios
AI simulations combine weather scenarios, consumption and generation data to accurately forecast supply and demand. This allows organizations to make faster and more informed investments in infrastructure and capacity.
Source: TU Delft – AI Effect (2024)
5. Customer service and forecasting
With AI analysis of customer queries, sentiment and usage data, we help energy suppliers respond faster and more personally. That makes for 30% faster processing and less customer turnover.
Source: IEA – Energy and AI Report (2023)
Sample cases
- Stedin: AI for predictive maintenance
Stedin uses AI to detect power grid failures early.
Using GeoAI and sensor data, models predict where maintenance will have the most impact, increasing grid reliability and avoiding unnecessary excavation.
- Eneco: Smart prediction of energy consumption
Eneco deploys machine learning to predict customers’ hourly consumption patterns.
With this, they optimize procurement, storage and delivery of sustainable energy. The result: less waste, lower costs and better service for customers.
- Greenport West-Holland: AI for energy and crop optimization
In greenhouse farming, AI continuously monitors and predicts temperature, CO₂, and energy consumption. This makes it possible to use energy smarter and maximize yields, sustainably and profitably.
Why choose DSL?
- 9 years of experience with data & AI within public, semi-public and commercial organizations
Whether you manage grid, supply energy or produce: the future is data-driven.
We help your organization integrate AI strategically, responsibly and scalably.Schedule an introductory call
Discover how data and AI help accelerate your energy impact, from asset management to customer value.
Cases AI in healthcare
View some of our healthcare case studies here:
- Instant access to contract information and policy conditions at the pharmacy counter by our virtual assistant
- Improved flow in the emergency room through our AI solution that predicts whether a patient needs to be admitted
- Safe and efficient implementation from Machine Learning models at the care
- Influence from classic risk factors at cardio metabolic diseases investigated
- Understanding data maturity as a foundation for future-proof healthcare innovation
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What do you want to do with data?
