Seeing Wind’s Problems with ‘Digi-eyes’

As the collective pursuit of net-zero accelerates, nations across the globe are facing increasing pressure to support the development of renewable energy infrastructure that can drive low-carbon economies. Wind continues to hold up in the energy mix but its challenges to fast scale-up are becoming more known, especially with regards to turbine reliability.

Transformative growth across the physical supply chain within the wind industry is already evident – installed wind capacity globally reached 906 GW in 2022, with forecasts indicating a further increase of 680 GW in the next five years, according to GWEC’s Global Wind Report 2023.

However, the race for scale in the past decade is notably having knock-on effects on operations and maintenance (O&M) strategies as the supply chain races to keep pace. As windfarms increase in size and components increase in complexity, recent reports highlight a correlation between the deployment of larger, modern wind turbines and rising mechanical issues that lead to unplanned downtime. This can prove costly to operators, with decreased energy production and component replacements seeing some making early exits with reductions in profitability.

As such, the rapid development and adoption of the digital supply chain continues to be a lifeline in addressing these issues. To some extent, the acceleration of digitalization has been similar to that of physical supply chain developments; as the wind industry faced new challenges, digital innovators and suppliers evolved to solve them. Demands for increased output as well as enormous scaling of the industry including new challenges in offshore and floating offshore wind has meant that pressures on the need for technological advancements in software has also increased, including the development and deployment of advanced data and analytics in predictive maintenance (PdM) solutions.

Data Driven O&M

Predictive maintenance technologies aim to prevent unplanned downtime and reactive unscheduled maintenance by providing accurate data on asset health for owner/operators to make the best decisions for their fleet. These solutions provide overviews of turbine performance across the breadth of a windfarm, providing early indications of component faults before these become critical and result in turbine failure. By fueling data-driven decision making, advanced data sensing can optimize fleets and support effective asset management, ensuring efficiency in performance and production to boost profitability.

ONYX Insight’s own research has found on average, a 100 MW wind farm can produce 200 false alerts per year, resulting in approximately $200,000 in technician labor costs, transport to turbines and lost revenue during downtime. However high-quality predictive maintenance using advanced analytics can reduce those false alerts by 93 percent.

But aside from the clear benefits operationally, they also give investor confidence. Accurate data can provide a much-needed boost to the industry by providing data for better decision making and long term strategic planning.

The introduction of PdM as a key component of windfarm O&M strategy is also contributing to the profitable life extension of turbines. This is particularly relevant in more mature wind markets, such as those in Europe, where ageing turbines are beginning to meet the end of their design lifespan at 20 to 30 years and require continued maintenance and management during life extension.

By retrofitting condition monitoring systems on older turbines wind farm operators can modernize and extend lifespans through the adoption of detailed analysis and affordable monitoring. Replacing individual components when efficiency starts to deteriorate avoids catastrophic failures and unplanned downtime as far as possible, thus increasing the return on infrastructure investment.

Increasingly operators are encountering a struggle with too much data, which is unfiltered and difficult to interpret. Multiple data streams across turbines can be difficult to link together and turn into action plans for engineers, meaning the most effective maintenance is not always prioritized. At the same time, there are differences in the taxonomy and functionality of different CMS tools which can lead to data integration challenges.

More recently, there is growing adoption of more ‘holistic’ approaches to PdM which combines sensor technology with drone inspections and periodic internal inspections to encompass the whole turbine, and not just individual components. This is driving even greater efficiencies and cost savings for operators. As wind farms continue to increase in size and move farther from shore and into deeper waters, O&M is more challenging whole turbine PdM enables a safer, more reliable view of assets, allowing for early detection of potential faults before they become serious and maintenance to be scheduled.

Supply Chain Collaboration

Moving forward, the need to obtain value from excessive data streams through integration, automation and simplification must be prioritized. Specialized solutions for individual components within wind turbines can provide a more complete health assessment overview though the focus must shift to packaging these solutions into coherent decision-making processes. As a result of aggressive project portfolio growth and increased turbine sizes the digital supply chain must streamline and standardize its outputs to allow operators to make data-driven decisions with ease.

Collaboration is a key element to the continued development of predictive maintenance strategies which remain fit for purpose in the expanding wind industry. This has been observed already, with digital solution providers combining their technologies to be able to integrate that data and deliver value on a much larger scale to operators’ efficiency. Increasingly, the future of windfarm operation and maintenance will be data-driven and crucially, encompass whole turbine fleets, monitoring all components with integrated systems from single providers.

The strengthening of the wind industry’s digital supply chain will be of the utmost importance as looming global net-zero targets are approaching and owner/operators manage their reliability while keeping the cost of LCOE down. As operators seek to improve project efficiency while reducing cost and financial risk, the answer lies with the right predictive maintenance strategies.

For these technologies to be deployed effectively across the world’s windfarms at pace, continued investment, data integration and system streamlining are essential to accelerate their effectiveness.