Currently valued at US$600 million, Australia’s wind turbine and maintenance market is projected to reach US$1 billion by 2032, off the back of the nation’s growing rate of renewable energy installations.
According to research by Fortune Business Insights, rising investments in alternative energy sources will have a positive influence on the wind farm services sector in coming years, as demand grows for regular monitoring of key components ‒ including blades, generators and gear boxes.
Wind was Australia’s leading source of clean energy in 2023, representing 39.4 per cent of the country’s clean energy and 13.4 per cent of Australia’s total electricity. This share is projected to grow as the country’s strong winds and coastline provide ideal conditions for wind turbine installation, along with advances in technology, meaning wind power is also becoming more efficient and cost effective.“Wind power will play an important role as thecountry attempts to reduce its carbon footprint and move toward a sustainable energy future,” FortuneBusiness Insights noted.
“With continued investment and innovation,Australia’s wind industry will significantly contribute to the country’s clean energy goals in the coming years, creating a more sustainable future.” However, the operation and maintenance costs of wind farms, which can represent up to 35 per cent of the total lifecycle cost of a wind power project, pose a challenge.
The life expectancy of a wind turbine is estimated at about 20 years, and on average one week of down time per year is required due to maintenance. However, unexpected or unplanned shutdown of turbines incurs substantial costs, with more than 3800failures being reported annually, especially considering the logistical challenges of remote locations and the time required for component replacement and on-site repairs.
These types of repairs dominated the Australian wind turbine sector in 2024, but industry proponents are becoming increasingly more mindful of the consequences and costs of managing this.
Failures of wind turbine components and unscheduled downtime leads to higher maintenance and repair costs, with any repair or replacement of large parts often requiring expensive rental of cranes and other equipment.In addition to these costs, it has been estimated that unexpected downtime for a 500 MW offshore wind farm can result in production losses of approximately AU$19million per year.
Therefore, by reducing these costs through early detection of failures and decreasing downtime, losses can be minimised and the system’s operational life canbe extended.
To ensure effective management of wind farms, wind turbines are scheduled for maintenance every 2,500 to5,000 hours. These maintenance activities include oil level checks, lubrication of moving parts, blade tests, and replacement of worn-out gears. This type of service plays a key role in minimising turbine downtime and maximising power output and is therefore the biggest market for wind farm maintenance providers currently.
However, relying solely on scheduled or even preventative maintenance is insufficient to detect and predict conditions and anticipate potential failures, especially so for turbines installed in the 1990s and early2000s and are approaching the end of their lifetime.
Adopting effective methodologies and tools that assist in this process can significantly benefit wind farm owners by increasing energy production, availability and cost savings.
Since the complexity and size of wind turbines make traditional maintenance and inspection methods challenging, it has led to increased investments and the use of drone technology, automation, artificial intelligence (AI) and machine learning.
AI, for example, is playing a key role in improving power generation efficiency and reducing costs, thus ensuring timely maintenance and prolonged turbine lifespans.Meanwhile, drones can be equipped with a varietyof sensors to perform visual, thermal, LiDAR, and ultrasonic inspection.
Traditionally, these inspections would require personnel to enter hazardous zones and working at heights, exposing them to significant risks of accidents and injuries. Besides the safety aspects, drone inspections significantly reduce inspection time and associated costs compared to manual inspections.
When combining this with condition monitoring systems which use machine learning techniques to analyse wind turbine data and identify deviations from normal behaviour, or condition-based maintenance which involves ongoing surveillance and the detection of emerging faults, detailed data can be obtained, with software tools able to analyse and generate comprehensive reports.
These reports provide detailed insights into the condition of each wind turbine, including identified issues, severity levels, and actionable recommendations for maintenance or repairs.
The early deterioration of wind turbine systems and sub-systems can also be detected using their physical models or building models from their generated data.Identifying the root causes of failures leading toturbine downtime is essential in reducing inactivity and promptly addressing critical failures.
The physical model approach is useful for determining and capturing how the various components of turbines work. These monitored components are modelled into systems of physical equations that describe their behaviour from a thermodynamic, electrical, or mechanical perspective.
As technological developments continue to boost operational efficiency and reduce maintenance expenses, the cost of wind energy is projected to decrease, with experts expecting costs to drop from 17to 35 per cent by the end of this year and from 37 to 49per cent by 2050.
Despite these efforts however, the high cost of maintaining and upgrading wind farms as they reach the end of their operational lifespan can be prohibitive.
Pacific Blue recently announced that its18.2-megawatt (MW) Codrington wind farm in Victoria will be decommissioned by 2027, citing the major cost of repowering the site as the main reason.
Commissioned in 2001, the farm has already been in operation well over the average two-decade lifespan.As the wind turbines approach the end of their design life, a site upgrade would require new foundations to support the much bigger wind turbines that are installed nowadays and upgraded infrastructure to support the additional power to the grid.
The farm’s current turbines, designed in the 1990s, are rated at 1.3 MW each with a height of 81 metres. Modern turbines, by contrast, are rated between 6 MWand 8 MW, with heights exceeding 200 metres. Furthermore, the cost of replacing a single turbine could range between $3 million and $5 million.According to the operator, all these aspects mean it is a non-financially viable project
