What challenges did Vestas face before AI implementation?

Optimizing turbine configurations and energy output. Handling large volumes of atmospheric and climate data. Slow traditional on-premises computation methods. Need for improved scalability and cost effectiveness in renewable energy.

What was the impact of the AI solution?

Streamlined turbine simulations significantly. Improved cost efficiency for renewable energy efforts. Accelerated development cycles of compute-intensive tasks. Enhanced insights into climate and geographical factors.

Source

MicrosoftWent dark

Vestas enhances wind energy optimization using Azure

Use case typeEnergy optimizationUpdated Jun 13, 2026

Vestas, a wind energy leader, has implemented Microsoft Azure and . NET for their Vestas Turbine Simulator and Climate Library. The Turbine Simulator processes vast volumes of data like atmospheric conditions and turbine specifics to determine optimal turbine configurations. The Climate Library stores historical geospatial climate data to provide insights into weather patterns, helping optimize energy output. Transitioning from on-premises computing to Azure, Vestas achieves efficiency, scalability, and cost reduction. Azure’s cloud capabilities allowed them to utilize up to 400,000 CPU cores, speeding up development cycles and compute-intensive processes, critical for driving renewable energy innovations.

Organization: Vestas
Industry: Energy & Utilities
Location: Denmark
Published: May 2025

Reported outcomes

Strategic outcomes

New product / capabilityOptimized turbine and grid configurationsBetter decisions & insightEnhanced climate and geographic insightsSpeed & agilityAccelerated development cyclesCost efficiencyImproved cost efficiency

Primary read

Use case focus

Showing 2 of 2

1Renewable energy optimization
2High-performance computing simulations in energy

Optimizing turbine configurations and energy output.
Handling large volumes of atmospheric and climate data.
Slow traditional on-premises computation methods.
Need for improved scalability and cost effectiveness in renewable energy.

Adopted Azure’s scalable cloud resources for high-performance computing.
Used Vestas Turbine Simulator to evaluate turbine and grid configurations.
Leveraged Azure to run up to 400,000 CPU cores for large-scale simulations.
Adopted the .NET framework for a multiplatform development environment.

Technologies

Azure AI Azure HPC Azure

Streamlined turbine simulations significantly.
Improved cost efficiency for renewable energy efforts.
Accelerated development cycles of compute-intensive tasks.
Enhanced insights into climate and geographical factors.

Architecture

Vestas processes atmospheric and turbine data using the Turbine Simulator on Azure's cloud platform, and stores historical geospatial data through the Climate Library for renewable energy insights.

Sources & evidence1

Went darkLost public footprint

The cited source is no longer reachable and the organization has no newer case. Not a claim the system was discontinued.