Wind power: How swarming tech can boost revenue

Wind energy projects are becoming increasingly sought after as an asset class. Year-on-year reductions on the cost of producing energy have put the sector at the forefront of net-zero strategies in key markets such as the US and UK, which are planning massive buildouts of their green energy infrastructure. According to the American Clean Power Association, the US has $3 billion in proposed infrastructure investments in offshore wind power alone.

The perennial opportunity for wind stakeholders is efficiency. With the volatility of wind resources, delivering a higher ROI is a key driver for wind farm operators. So, how can owners and operators squeeze more energy out of wind turbines while reducing expenditure in the long term?

One route to unlocking the full potential of wind assets is through transforming traditional approaches to asset optimisation. A cutting-edge technology called ‘swarming’ will underpin the optimisation strategies of the future and improve ROI for wind asset owners by boosting annual energy production.

Wind asset challenges

Wind industry stakeholders need their assets to run at peak capacity. If wind farms fail to deliver as predicted, investors may start to view wind energy as riskier, which will increase the cost of credit for new-build projects. Wind has significant potential to deliver, but the industry needs to tackle its AEP deficit now, before it becomes more costly to fix as wind turbines and projects increase in size.

Industry estimates from the US National Renewable Energy Laboratory and other sources suggest fleet-wide losses of 5-20 percent of potential power production, due to common issues such as wake interference and yaw misalignment.

Existing solutions in the market have not tackled the problem of underperformance losses through a collective or plant-wide approach. Without suitable tools, operators are led to optimise wind assets on a turbine-by-turbine basis, similar to the strategy used for rotor blade extensions or repowering. This approach can only deliver incremental AEP improvements for asset owners. To drive significant revenue increases, the sector needs a systemic transformation of wind farm optimisation.

Autonomous future

Swarming technology, brought to the market for the first time by WindESCo, connects wind turbines in a wind farm, allowing them to react to neighbouring assets and changes in wind properties in near real time. Through swarming, turbines will automatically switch their operational profiles to optimise production for the entire wind farm instead of individual machines.

“Wind energy is rightly becoming a robust industry as it scales up globally”

By understanding how their operation is impacting the performance of the site at large, the solution enables wind assets to take predictive and protective turbine control measures for maximised fleet-wide production. Ultimately, this will help wind asset managers transition from defensive, or risk-based, approaches to offensive, revenue-producing solutions.

By embracing swarming to unlock hidden value in their assets, wind investors can expect 3-5 percent AEP improvement annually and a 3-4x return on investment over two years. For a typical 1GW wind plant, this would translate to more than £14 million ($20 million; €17 million) over five years.

Wind energy is rightly becoming a robust industry as it scales up globally. But what worked for a fledgling industry may not be right for a mature one, especially when it comes to optimising assets to extract extra value. The key to transforming ROI for wind investors is scrutinising traditional operational strategies and seeing how new technology can open up new possibilities for a truly co-ordinated future.