Previously, SKF announced that they had acquired Presenso Ltd. – a company that specializes in artificial intelligence (AI). Adopting data-driven technology presents wind farm operators and OEMs with plenty of opportunity to boost efficiency and reduce costs. So, how does this work in practice?

Wind energy is currently in competition with other electricity sources – both renewable and non-renewable – to establish itself as the world’s leading power source. Only by offering cost-effective, reliable energy will this goal be realized. Increasing power density may give the sector a competitive edge.

Global developments have strengthened the business case for AI-driven industrial analytics in wind farms. Predictive maintenance helps wind energy businesses to operate self-sufficiently, extend asset health and lifespans, reduce O&M costs, and better protect repair crews.

Wind turbines are usually designed to operate at high wind speeds to produce as much power as possible. But in certain regions, such as inland sites in South East Asia, wind speeds are lower – making conventional turbine models unviable. This is where innovative wind turbine design comes into play.

The promise of wind energy is now a reality. From Gansu, China to Hornsea in the United Kingdom wind farms are producing a larger share of energy than ever before. But there is one piece of the puzzle missing: storage. How can companies get the most out of renewable energy?

Artificial intelligence (AI) already plays a role in many aspects of industry, including supply chain management, product development, and maintenance planning. Companies must evolve with the changing industrial landscape and use the tools at their disposal to maintain their competitive edge. What does AI offer wind energy?

Understanding for how long a bearing will be operational is vital for planning wind turbine maintenance and budget allocation. Therefore, this information is key for operators when selecting the right component for their application. Calculations based on statistical models are used to estimate bearing rating life. In this article, the Wind Farm Management Blog analyzes how this process works.

In recent years, drones have become much more present in our society. They are used for tasks such as homeland security, shooting videos, and plans are even in place for them to deliver packages. This trend is now coming into action in the wind energy sector.

Big data, remote monitoring, and process automation are becoming more prominent in wind energy. As a result of many systems and machines being networked, the likelihood of cyberthreats increases. What can operators do to protect wind farms in the digital age?