The wind power sector has been scaling up, with the installed capacity exceeding 42,633 MW as of March 2023. A key issue in the wind energy segment is the high operations and maintenance (O&M) costs. These constitute a major chunk of the total annual costs of a wind turbine. For a new turbine, O&M costs may account for 20-25 per cent of the total levelised cost per kWh produced over the lifetime of the turbine, according to TWI Limited. While the share might be 10-15 per cent initially, it increases with time.
As a result, manufacturers are attempting to lower O&M costs by incorporating automation, which reduces the need for manual service visits as well as turbine downtime. Within automation, artificial intelligence (AI) is gaining traction across different processes in the renewable power industry. Due to this, several challenges pertaining to O&M of the wind segment are being addressed.
The following are the key automation trends in the wind energy space:
SCADA systems
Supervisory Control And Data Acquisition (SCADA) is a type of software application used to regulate industrial processes. It collects data in real time from remote locations to control equipment and conditions. It thus allows for complete remote control and supervision of an entire wind park, as well as individual wind turbines. SCADA systems can provide a comprehensive view of all key wind turbine characteristics, such as temperatures, pitch angles, electrical parameters, rotor speeds and the yaw system, for peak performance.
Thermal camera for blade inspection
Thermal imaging is a technology that allows operators to inspect a wind turbine’s electrical and mechanical components, along with the surrounding electrical systems. The general rule for both kinds of components is that it will heat up before it fails. Thermal imaging cameras help in detecting this temperature rise before a malfunction occurs, as the hot regions are visible in the thermal image. A thermal camera may also help detect gearbox and motor problems such as shaft misalignment, and electrical problems such as loose connections and uneven loads.
Software for ice detection
Atmospheric ice has a considerable impact on the operation of wind farms. To achieve peak performance, a turbine must detect ice on the rotor blades as soon as it appears. It must then send a signal once the rotor blade is clear of ice, indicating that normal operation can resume. There has been a rise in software that facilitates reliable ice detection for rotor blades, in a bid to increase the yields of wind turbine generators.
Future outlook
Automation can help improve output efficiency and reduce the associated costs of power generation. The application of AI for automation has been increasing. AI comprises a collection of methods or algorithms that use data to learn rules or patterns, thus continuously improving with new data. AI is increasingly being used in wind O&M to improve efficiency, and reduce downtime and unscheduled maintenance costs. Further, AI is helping wind farm O&M to become predictive and automated.
Incorporating AI with wind power generation ecosystems has multiple uses. It allows better forecasting, as AI sensors can perform continuous analysis of massive amounts of environmental data. It allows accurate prediction of, and real-time adaptation to, weather and wind conditions. This improves planning and operational efficiency, and eliminates unnecessary shutdowns due to weather or environmental threats.
The use of AI can also ease the execution of O&M activities, as such systems can uncover patterns signalling the need for future maintenance and repair by monitoring wind conditions and referencing data from records of prior maintenance. This data can then be used to develop an optimised schedule, specifying when and how frequently maintenance should be conducted.
Moreover, AI-powered technologies can be used to monitor turbine performance in real time and to automate turbine inspection. Such technologies frequently disclose errors that human inspectors may not catch physically. Despite the high initial costs of adopting these technologies, the long-term project life cycle gains they offer are high. With the current rate of innovation, automation and digitisation are expected to change the face of wind power O&M in a few years.
By Nikita Choubey
