For wind farms to thrive in a subsidy-free market, a shift change to the industry’s convention of "end of life" is necessary. Life must now be optimised on a balance of economics and engineering risk of failure, rather than the pre-determined 20 years. Instead, end of life should be considered more flexibly,based on market conditions and evolving technologies. There is a high potential of uplift in value by optimising the lifetime assumption through smarter operation as its catalyst, driven by innovation in dynamic control and data analytics.
The concept of extending the lifespan of renewable-energy assets where capex is high, opex is relatively low, and "fuel" is free, is not new. Some hydro-electric plants have now operated for close to a century with carefully managed maintenance and retrofit programmes. So, can we extend operating wind farms to 30 or even 40 years? The answer is most likely yes, depending on how operational risks are managed and which components are treated as consumable rather than critical infrastructure.
Owners are starting to assume they will operate their assets for longer and are changing their financial models to reflect this. In January, Greencoat UK Wind, announced to the London Stock Exchange that it was changing the net asset valuation assumption of its portfolio from 25 years of life to 30 years on a conservative basis. This type of decision is increasingly being made when turbines are in their infancy, supported by calculations showing that there is "headroom" arising from the selection of type-certified turbines. When this headroom is coupled with accurate operational measurements and refined load calculations, this can add to lifetime expectancy.
Investors will only be comfortable agreeing to longer loan terms if the industry can demonstrate that robust engineering calculations are supported by risk mitigation through refurbishment provision and inspection management programmes.
A useful approach to extending asset life is an integrated methodology that addresses two key questions faced by project owners: "how much fatigue capacity remains in my asset?" and, "how can I best utilise it?". Cost models designed to evaluate a range of lifecycle strategies are based on a data-driven framework to assess options such as turbine-control modifications, project-wide control policies, and O&M approaches. Simulation modelling and data analytics are complemented by targeted inspections of components.
How to approach life extension
Managing operational risks is at the centre of this methodology. For example, on a wind farm where each turbine is of identical design, some machines will experience higher fatigue loading than others. Smarter control upgrades mean that loading can be more evenly distributed over a wind farm. Techniques such as wake steering, where a turbine is actively yawed to steer the wake away from a downwind turbine to limit loads, are being developed and will be available in the near future.
Smarter maintenance may see the operator swapping higher loaded components between turbines to more evenly distribute fatigue. Swapping the blades from the most loaded turbines at midlife with blades from the least loaded will reduce the extremes of fatigue life. Also, as the risk of failure of components increases with time, implementing intelligent risk-based inspection and maintenance programmes mitigates risk.
To gain confidence in approaching such matters, owners and investors will look to international standards. The IEC Technical Specification on Life Management and Life extension of wind turbines (IEC 61400-28) is still under development. Until this is available, the industry is reliant on frameworks and guidance put forward by institutions and companies.
As an added complexity, during the energy transition to high renewables penetration and lower energy prices, wind farms will no longer operate in a passive, predetermined way on our grid systems. They will be required to be more flexible and dynamically controlled to help maintain system integrity and respond to market conditions and operating at part load will become more frequent. Such changing operating strategies will lead to a need for fatigue life projections to be continuously re-evaluated.
This new era is seeing the emergence of wind-farm digital twins that model and project the impact of operational changes on lifetime assumptions. The wind industry must now challenge convention, and embrace innovation to get investors’ confidence for longer life.
Keir Harman is director of renewables operations at DNV GL