According to a study by DeLoitte, wind turbine operators are set for significant growth over the next few years as governments increase their investments in renewable energy. As business improves for the wind energy industry, the need for efficient maintenance practices and cost-saving devices will become more and more pressing.
Predictive maintenance routines are among the most forward-looking solutions in this regard. Wind farm operators would be doing themselves a favor by leveraging them as much as possible as they seek to improve efficiency. This is especially the case when you consider the sheer scale of wind farms. A single wind farm can have thousands of turbines. The internet of things (IoT) – of which predictive maintenance tools are an extension – is really the only way that individual turbines can be monitored and maintained.
What is predictive maintenance?
Predictive maintenance uses monitoring tools to track a wind turbine’s performance and condition and predict possible failures before they arise. This practice helps operators keep their turbines running at their peak consistently, as they can eliminate faults before they have a significant effect on output. This reorients maintenance from being calendar-based – where maintenance is carried out in specific time-frames – to condition-based, where maintenance work is done in response to feedback from the monitoring tools.
What are the benefits of predictive maintenance?
By gaining the ability to continually monitor wind turbines, operators can tackle wear and tear and mechanical breakdown proactively and thus reduce degradation and prevent unplanned downtime. This will also help to extend the lifespan of turbines and optimize their efficiency. This all has a favorable effect on operation and maintenance costs. Less downtime and the prevention of large-scale repair and replacement work, wind farm operators can keep costs at manageable, predictable levels.