The power of big data I Siemens Gamesa (2024)

Digital expertise that keeps your wind turbines turning

Data learning drives the wind industry into a new era

The future of the wind industry will not be business as usual. How are big data insights powering a new era of smart wind power and transforming the entire digital enterprise, accelerating innovation, and harnessing new opportunities?

By the year 2020, the volume of digital data stored is expected to surpass 40 zettabytes. One zettabyteis 50 percent more than all the grains of sand on all of Earth’s beaches – an astronomical amount of information with equally momentous potential. Yet, big data is not new to the wind industry.

The sector granted connectivity to turbines over a decade ago, with some companies installing sensors as far back as two decades ago. From energy outputs to weather conditions, these sensors have recorded nearly every factor of operation. Now, the question becomes how to translate the mountains of amassed data into meaningful insight – a transition that will accelerate renewable energy innovation.

The key to creating really smart wind turbines lies in the future – literally speaking. As turbine sensors continuously transmit data to Siemens Gamesa’s Diagnostic Center, a digital model uses these values to forecast the condition of the physical asset.

These models examine weather, component information, service reports and the performances of similar models in the global fleet to determine when and how a turbine should be serviced – days, weeks, months, and even years in advance. This predictive capability reduces unplanned maintenance and downtime, adding weeks of profitable production.

In the future, a digital wind farm’s success may hinge on these aspects:

• how skillfully its virtual model has been designed
• how successfully operational data can be fed into it
• how well the resulting data can forecast its future.

At the Diagnostic Center, 130 analytic experts perform more than 34,000 data analyses per year. Vibration diagnostics detect irregularities indicative of potential fast- or slow-developing damage, and over 99 percent of all drive train damage is accurately predicted. The advantage of this digital service lies in the savings and the planning: New parts can be ordered in advance and servicing can be postponed until the low-wind season.

When the technician visits the site, our Monitoring Operations and Registration System (MORS) provides a report outlining the issue and data-driven solutions. For every turbine event that occurs, whether reactive or proactive, a diagnostic MORS case is recorded – in a database that now contains over two million cases. Each case generates advice on the immediate remote handling of the turbine by analyzing data from previous cases. With a database this diverse, Siemens Gamesa can remotely resolve 85% of all alarms received within 10 minutes.

Big data in wind energy introduces an opportunity to boost performance through advanced technology. As the Original Equipment Manufacturer (OEM), Siemens Gamesa uses operational sensor data to create solutions that respond to specific turbine and customer needs. In fact, 80% of Siemens Gamesa’s data-driven applications are standalone, enabling customers to generate more energy from the same infrastructure. Three examples of how data-driven upgrades optimize assets for the lifecycle of the project:

• Power Curve Upgrade (PCU): a three-part package that improves a wind turbine’s ability to utilize the wind by enhancing the blade surface
• High Wind Ride Through (HWRT) functionality: stabilizes energy output under extreme wind conditions – when a certain threshold is met, the system automatically moderates production, preventing the turbine from shutting down
• Operation With Ice (OWI): a solution performing remote adjustments of blade pitch and speed to maintain steady operation in harsh climates