How to Maintain a Wind Farm

We can’t avoid it—breakdowns in wind farm turbines happen from time to time. The resulting loss of revenue is very costly. Productivity and work output decline, and expenses for materials, personnel, and outsourced services increase… In some cases, these breakdowns can even pose risks to people, particularly in the event of very serious accidents. For this reason, maintaining a wind farm is crucial to its proper operation.

To the extent that companies implement a predictive maintenance plan, they can better plan for uptower maintenance and reduce insurance premiums. The company benefits by being able to anticipate problems. Failures can be detected months in advance, allowing ample time to plan repairs. This prevents machine downtime during periods of high availability.

Ultimately, you’ll be extending the useful life of your assets and generating significant savings.

At Grupo Álava, we combine the experience of a company with more than 25 years of experience in predictive maintenance with new technological solutions that enable advanced data analytics and are focused on the Digital Twin.

We automate fault prediction using a tool that allows us to configure relative and statistical alarms, as well as anomaly detection for groups of assets, enabling us to detect any deviations that actually occur in the machine.

We anticipate failures by ensuring the machine remains in good working order at all times and diagnosing the root cause of any failure. All of this is made possible by a team of analysts with extensive experience in the industry.

We offer highly specialized solutions designed for predictive maintenance and extending the service life of wind turbines, transformers, and other equipment. We enhance early detection and diagnosis capabilities by integrating various information sources, including different CMS and SCADA systems. We utilize high-level KPIs to ensure proper asset monitoring. All of this is supported by a highly specialized technical team with extensive experience in predictive maintenance for wind turbines..

Maria José Gómez, Business Manager – Predictive Maintenance at Grupo Álava)

You can choose to move toward automation using algorithms, machine learning, and anomaly detection. We can integrate various predictive techniques: vibration analysis, oil analysis, and electrical systems. All of this is included in a single solution. We maximize the value of all integrated data to perform an accurate analysis of your assets.

Thanks to our IoT platform, we bring together various data sources into a single interface. We standardize their processing and employ a series of advanced algorithms to extract value from them.

You’ll have access to a flexible digital model. You choose which variables you want to control, the algorithm to apply, and the type of response required. You’ll be able to maintain your wind farm by extending the useful life of your assets.