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Predictive Maintenance for Renewable Energy Assets

Technology Overview

This technology offer is an industrial IoT (IIoT) based predictive maintenance platform for renewable energy assets. The technology owner has a portfolio of over 5000 turbines, from 18 manufacturers and 52 models and 20 years of data. With this best-in-class proven technology, failure predictions can be made 12 months in advance, to the component-level, with an accuracy level of 99.9% and without installing any hardware. This technology offer is based on more than 5 years of research in artificial intelligence (AI) and predictive modeling, and is proven on more than 5000 industrial assets. Asset optimization is brought to the next level by creating a digital twin of each component. This technology is able to optimize operations and maintenance, increase machine efficiency, enable real-time monitoring, and forecast assets' conditions.

Technology Features, Specifications and Advantages

Advantages

The approach used for this technology offer is based on combination of 3 different modelling techniques, creating a Digital Twin of each component in the renewable asset:

  1. Physical Modelling
  2. AI Modelling
  3. Normal behavior Modeling

The complementary interaction of these modeling techniques allows the digital twins of all main components to detect underperformance and its root causes, as well as to provide concrete maintenance recommendations.

While the value is created in the backend of this IIoT-based platform, the results can be consumed via a dashboard, or integrated to the client’s overall system using smart API.

In addition, this technology is also adaptable to other industries due to the similarity of mechanical and mechatronic components and their behavior.

Potential Applications

This technology offer is adaptable to several industries (strategically aligned to the renewables sector) due to the similarity of mechanical and mechatronic components and their behaviors.

  • The primary application area is the wind energy industry.
  • Can be also applied in the solar energy sector, green hydrogen, hydropower, and production machinery.
  • More green energy can be produced and OPEX saved.
  • Global (TAM, SAM): 1 212 000 MW installed capacity, Asia (SOM): 496 920 MW (41%).

Customer Benefits

This technology offer helps especially wind farm operators cut their OPEX by 50% while increasing energy production by 15%.

  • This technology optimizes renewable energy production, reduces assets visits, downtime, and lost profit; therefore increases green energy production.
  • By increasing green energy production, this technology contributes to the sustainable development of the energy industry and helps to reduce CO2 emissions.
OVERVIEW
Contact Person

Dana Sultanova

Organisation

ANNEA.ai GmbH

Technology Category

  • Energy
  • Performance Monitoring System & Sensor, Solar, Wind & Waves
  • Environment, Clean Air/Water

Technology Readiness Level

Keywords

predictive maintenance, digital twins, performance optimisation