ACCESSIBLE AND EASY TO USE
When you sign up, the WindGEMINI team takes care of all the set up and, once data start flowing into the system, our data driven insights become available immediately and are accessible 24/7 via our Veracity portal. Automated alerts let you know when something requires your attention.
COST EFFECTIVE
Our subscription plans are tailored to the size of your wind farm. The price is a fraction of what the engineering effort required to produce the same data-driven insights generated by WindGEMINI would cost. All algorithms are based on SCADA data, making use of what is already available without the need for additional sensors.
DEVELOPED BY EXPERTS
The algorithms in WindGEMINI are based on over 30 years of experience of our Data Analytics department, who have assessed over 60 GW of wind farms across the world, and of our Turbine Engineering Support department, who have been involved in the design of over one hundred turbine models.
| Example | Introduction |
|---|---|
Example |
IntroductionOur frequency analysis algorithms process higher frequency data from standard turbine interfaces to help detection of structural issues such as rotor imbalance and foundation degradation, which can be mitigated to reduce operating costs, increase energy capture and extend turbine life.
|
| Introduction | Example |
|---|---|
IntroductionDNV’s artificial intelligence algorithms analyse SCADA data to identify power curve performance issues, incorrect turbine control settings, and sub-optimal operation so that these can be rectified to increase top line revenue.
|
Example |
| Example | Introduction |
|---|---|
Example |
IntroductionThrough monitoring the relative variation in production between turbines and over time, it is possible to identify performance outliers and degradation in turbine performance, so that these can be corrected. Our Pattern of Production Analysis can also be used to validate performance upgrades.
|
| Introduction | Example |
|---|---|
IntroductionThis module combines the analysis of SCADA data from the wind farm and of mesoscale reanalysis data to estimate the contribution of windiness, turbine availability and performance to any difference between actual production and operating budgets. Where sufficient data are available, the algorithm uses the long term mesoscale data to generate long-term annual energy yields.
|
Example |
| Example | Introduction |
|---|---|
Example |
IntroductionThis module leverages DNV’s physics based simulation models to calculate fatigue accumulation at the main structural components. This provides an estimate of the remaining life of a turbine which can be used to identify opportunities to extend life and prioritise inspections and maintenance. The life calculations are based on DNV’s aeroelastic modelling software Bladed, the industry standard solution for the design and certification of wind turbines.
|
