What if you owned a wind turbine that could self-diagnose a gearbox vibration it detected and ‘call home’ to a remote monitoring operations centre to ask for an oil change? The wind energy industry is only a few years away from the digital industrial revolution having a major impact on the way in which the industry operates and generates revenue.
By Philip Totaro, CEO, IntelStor
The push towards data creation and the ability to leverage it has resulted in some of the Tier 1 wind turbine OEMs pioneering new digital technologies and hiring or reassigning huge numbers of personnel to work in their new internal digital technology laboratories.
But many companies still need to consider the adoption of digital technology along with the new business models necessary to take full advantage of this push towards digitalisation.
What is Digitalisation?
The digital revolution is about creating a digital representation of a physical world, including the machines and the people who operate them. While that might sound like something from the 1999 film The Matrix, it's quickly becoming part of the real world. There are many different labels associated with different aspects of digitalisation, such as ‘Internet of Things’, ‘Industrial Internet’ and ‘Industry 4.0’.
In practical terms, an example of what this means to the wind energy industry is the development of computer models representing the full value chain – from an electric grid, to a wind park, to a wind turbine, to a gearbox, to the gears, bearings, lubricants and other internal components, and right down to the atomic level of the materials which make them all up.
Data Science Meets Materials Science
Being able to evaluate components based on their material composition and predict their behaviour when subjected to different operating conditions opens the door to new materials being developed or used for applications such as life extension or predictive maintenance scheduling.
On the macro level, a digital version of a wind park will be able to harness historical operating data (wind speed, power, yaw angles, gearbox temperature, etc.) and use the trend analysis for individual turbines or an entire fleet of turbines as input criteria to a predictive model.
A predictive model might tell us how the individual wind turbines or the wind park as a whole can and should be operated in order to achieve a specific goal. Such a goal might be to maximise power output to take advantage of time-of-day price arbitrage when feeding wind power into an energy storage system or implementing a life-extending curtailment mode of operation.
Digitalisation = Speed
Digitalisation could also enable service providers to be fed instructions from a central data processing server that has determined when a sequence of turbines in a wind park can be taken offline for service with the minimal impact to the availability guarantee. The central server would be programmed to look at current and future weather data, historical (seasonal) park production, remaining useful life of specific components, and the availability of spare parts in inventory at the maintenance facility.
Instructions on what components to inspect, repair or replace, and in what order to fix them, will be seamless. This information can be delivered to a smartphone, tablet or even a helmet that may have virtual reality or augmented reality technology to help facilitate the workflows.
Compare this new environment to 25 years ago when wind turbines may not have been networked or internet connected due to the cost. Deciding when a wind turbine needed maintenance meant driving to a site and visually inspecting the turbine.
Get Ready for the Renewable Energy ‘App Store’
So what's new and innovative about this? Digitalisation represents the first time in history when a single operator can have a fully integrated digital model that can be used to accurately predict the future. This allows them to control and shape that future with maximum profitability in mind.
Companies are seeking to develop a platform on which a host of capabilities can be offered. Both turbine purchasers and also asset operators who leverage the platform will be able to offer a range of capabilities, which is likely to result in an increase of independent asset operators.
Think of this scenario like an app store on your smartphone. You probably have apps developed by the owner of the store for some basic functions, but there are plenty more which are contributed by the industry community at large.
In our world, one module or ‘app’ would be for energy output optimisation, while another ‘app’ would be for ordering spare parts as part of a predictive maintenance scheduling programme, while yet another ‘app’ would be for calculating the remaining useful life of components by analysing their wear rate.
Whether the capability was provided by the OEM or a third party through the OEM platform, a content licensing and revenue sharing agreement is likely to be used. It will also become important to address data access rights by the platform holder for the content created and warehoused by the third party ‘app’ supplier.
Specifically, would a company such as GE get access to the data cultivated by an asset owner who is using a third party developed ‘app’ for price optimisation of energy output just because the capability was being delivered by the GE platform?
These aspects of the business models in the digital world are yet to be fully resolved, but they will become of critical importance as the industry drives towards a digital future.