Power and renewables

OUR ALGORITHMS

WindGEMINI is the most comprehensive advanced analytics system available for the wind industry. Its algorithms produce insights on wind turbine performance, power curve analysis, component failures, remaining life and even long term production forecasts.

Drivetrain Integrity Monitor

Introduction
Example
Introduction
A machine learning algorithm analyses turbine temperatures to identify patterns indicative of incipient failure modes and raise alerts that can be used by owners and operators to avoid failures, optimise servicing and inspections and reduce downtime.
Example
WindGEMINI service - Drivetrain Integrity Monitor 400x234pxl

Structural Integrity Monitor

Example
Introduction
Example
Structural Integrity Monitor
Introduction
Our 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.

Power Curve Performance Watchdog

Introduction
Example
Introduction
DNV GL’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
Power Curve Performance Watchdog

Pattern Of Production Analysis

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Introduction
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Pattern Of Production Analysis
Introduction
Through 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.

Energy Production Analysis

Introduction
Example
Introduction
This 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.
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Energy Production Analysis

Turbine Life Estimator

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Introduction
Example
Turbine Life Estimator
Introduction
This module leverages DNV GL’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 GL’s aeroelastic modelling software Bladed, the industry standard solution for the design and certification of wind turbines.

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