Data-driven operation and maintenance

In 2022, the cumulative capacity of installed wind power worldwide amounted to approximately 906 GW, with this number showing no sign of slowing down.¹

As capacity and turbine sizes increase, and wind farms move further offshore, owners and operators are presented with even greater challenges in maintaining their equipment to ensure ongoing productivity.

In 2020, the market for operations and maintenance (O&M) of wind turbines was estimated to be valued at US$15.4 billion. By 2031, this is expected to reach US$39.8 billion.¹

Reliability concerns continue to grow. Recently, issues around quality control led to Siemens Energy announcing that there had been a substantial increase in failure rates of wind turbine components. This resulted in its subsidiary Siemens Gamesa carrying out an extended technical review that will incur significantly higher costs than previously assumed, estimated to be more than €1 billion (US$1.09 billion).

While there may be specific issues for the German giant to deal with internally, they do not appear alone in tackling major reliability issues. Discussion around turbine failure rates is a welcome sign that OEMs and operators are focusing on challenges that are having a major impact on profitability. While these issues are difficult to fully resolve, their impact can be managed and reduced via investment in condition monitoring and predictive maintenance tools.

It is a symptom of a maturing industry that many large wind farms are now nearing the end of their planned 20-year design lives. Additionally, the rate of replacement of major components remains very high. Statistics show that in a typical operational wind turbine:

• More than 40% of gearboxes will have to be replaced in 20 years of project life.
• More than 20% of main bearings will have to be replaced within 20 years.
• More than 5% of blades will have to be replaced within 20 years.

While blades may make up a relatively small percentage of turbine failures, they are one of the most challenging and costly components to fix. They are undoubtedly one of the most exposed parts of any turbine, with the latest designs reaching over 80 m in length. Damage or faults that go undetected can have catastrophic results so early detection is critical.

Understanding blade failures

Blade failures can be categorised broadly as internal or external faults, and both pose different challenges. External failures are generally less critical to the structural integrity of the blade, and are typically identified through visual or drone inspection. With the turbines exposed to all elements, external damage is very common.

Damage to the blade tip can occur during lightning strikes and can lead to consequential delamination or cracks within the blade, rendering it non-operational until a repair can be performed.

Similarly, leading-edge erosion is also a frequent failure caused by continuous exposure to rain, dust and other airborne particles. As leading-edge erosion progresses, the blade surface can become increasingly rough, with greater drag affecting the aero-dynamic performance and power production of the turbine.

While external failures typically develop slowly, as blade sizes continue to increase, this creates a greater challenge for operators to manage.

Visual inspection is the most efficient and effective method for identifying external damage. Rope-access inspection is a common method but can be time-consuming and is often hampered by weather conditions. Drone technology has delivered significant improvements in recent years, and by tapping into autonomous drone solutions, inspection downtime costs can drop by 70 – 90%.

On the other hand, internal blade failures are much more complex and can affect the structural integrity of the blade. Additionally, the industry currently lacks widely accepted approaches to monitoring these types of critical failure mode. Internal cracks in the main spar or bond lines can develop very quickly, growing from a few centimetres to 1 – 2 m in length within weeks or even days. As the internal structure is load bearing, unlike external failure modes, the blade cannot keep running safely for a long period of time. For instance, the shear web – a structural element in the blade of a wind turbine that helps to transfer shear forces between the blade – can become dis-bonded due to stress, halting operations immediately.

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Energy Global's Autumn 2023 issue

The Autumn 2023 issue of Energy Global hosts an array of technical articles focusing on green hydrogen, wind installation technology, blade monitoring solutions, and more. This issue also features a regional report looking at some key renewables projects in Australia.

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