The summer and early autumn of 2021 saw Europe experiencing a long period of dry conditions and low wind speeds. While the bright, still weather was welcomed by many Europeans, lack of wind can be a serious issue when it comes to power generation.
Europe is undergoing an energy transition and, following the invasion of Ukraine, the case for a rapid clean energy transition has never been stronger. Policymakers are determined to slash the EU’s Russian gas dependence by increasing its reliance on renewables. While wind and solar are cleaner, they can be fickle, as illustrated by the sudden drop in turbine-generated power.
As European wind asset owners endured a summer of low wind, peak hour power prices have risen to their second highest level since 2018. In 2021, energy companies, including SSE in the UK and Ørsted in Denmark, reported their lowest wind speeds for two decades, with the pressure to deliver on production targets at an all-time high.
While wind farm developers are aware that these low wind ‘events’ are possible, understanding their impact has become a hot topic in
energy-meteorology research. In fact, the sixth IPCC report published in February suggested that average wind speeds over Europe will reduce by 8 to 10 percent by 2100 as a result of climate change.
Is it just down to wind?
In short, no. Wind energy operators may be incorrectly attributing reduced power generation solely to low wind speeds, rather than leveraging technology to investigate alternative reasons for wider underperformance.
If asset owners continue to attribute low power generation solely to wind resource, there could be a significant impact on wind portfolio valuations and investor returns, and reduced supplies of clean power to the grid. Comparably, a focus on turbine ‘availability’ – over maximised performance – may prevent asset owners investigating lower power outputs with more rigour. If the forecasted dip in wind speeds does happen, access to high-quality data will be vital in enhancing asset performance.
In the instance of lower power generation, there could be myriad other factors affecting project underperformance beyond low wind resource. This ranges from incorrect yaw or pitch settings, or unanticipated environmental factors.
Clir Renewables combines the world’s largest renewable energy operational dataset with advanced AI that is designed, built and supported by decades of renewable energy expertise. By benchmarking data from all major original equipment manufacturers, we can measure asset and turbine performance against region, vintage and technology to ensure that projects are performing up to industry standard. Access to 200GW of wind and solar data allows us to benchmark performance against industry standards. This offers investors and asset managers the opportunity to identify issues that may be misdiagnosed to maximise the financial returns and minimise risk of renewable energy projects.
While the software can identify low wind periods its true value is its ability to delve into the root causes behind wind farm underperformance irrespective of wind levels. We work with site operators to identify and resolve issues that, in many cases, are attributed to ‘low wind’ rather than wider inefficiencies.
To date, our technology has been deployed on wind projects globally, with the aim of providing deep insights into wind farm performance. A recent collaboration with Nuveen’s Glennmont Partners, Europe’s largest pure clean energy specialist, saw Clir investigating seasonal underperformance which was detected during an analysis of the project’s supervisory control and data acquisition (SCADA) data.
Clir’s in-depth analysis confirmed Glennmont’s initial findings and outlined in detail instances of underperformance that were likely related to software changes implemented by the wind turbine OEM.
“While the software can identify low wind periods… its true value is its ability to delve into the root causes
behind wind farm underperformance”
Clir, in tandem with Glennmont, facilitated a constructive and positive working relationship with the OEM, supporting technical analysis and commercial discussions. This ensured productive collaboration to determine the best solution – in this case the addition of extra vortex generators. Following the implementation of the additional vortex generators, which Clir later validated, the upgrades demonstrated a 2.9 percent increase in project annual energy production. An increase of this size can significantly improve the economics of projects through better insurance and financing terms.
Implementing machine learning to analyse multiple data streams, including near real-time and historical SCADA data from the turbine and grid, alongside geospatial and weather records, allows us to pinpoint whether seasonal underperformance really can be attributed to low wind resource, or whether the issues stem from factors such as environmental interference or fixable technical errors. This insight can then be used to inform operations, model future revenue and identify opportunities to negotiate existing terms on debt financing or insurance based on forecasts backed up by real project data.
We know that significant marginal gains can be made by immediate reporting and acting on equipment issues to optimise wind assets. By continuing to place blame for lower performance solely on wind resource, we’re collectively missing a huge opportunity to increase wind energy contributions to the European power mix, and the underlying value of projects and portfolios.
What does the future hold?
With energy demand surging and emissions from the power sector at a record high, the International Energy Agency has called on governments around the world to accelerate plans to move to low-carbon technologies such as wind power. The IEA expects a return to historical average wind speeds in Europe, with renewables growth crowding out fossil fuels over the next three years as prices continue to decrease.
Last year saw a surge in investment in climate technology and assets. In the current market conditions, investors continue to show confidence in green energy which, according to The Wall Street Journal, wasn’t present 10 years ago during the last green bubble. This confidence continues to grow and can be evidenced through the likes of ScotWind – Scotland’s flagship offshore wind auction, which set the country at the forefront of the development of offshore wind.
Netting almost £700 million ($912 million; $841 million) for Scottish government coffers, the 17 new projects provide some of the biggest names in global energy with massive new development opportunities with a combined potential generating capacity of 25GW.
As renewable energy projects continue to increase in size, they must continue to take advantage of the sheer amount of data present. Properly utilising and analysing this data will better allow asset managers to maximise efficiency during low-wind periods, with gains for consumers and investors alike.
With power prices and the energy sector’s emissions rising to unprecedented levels, additional market volatility and continued high emissions will be inevitable over the next three years unless the sector invests in renewables and energy efficiency supporting data.
Gareth Brown is CEO of Clir Renewables, a Vancouver-based company that uses software to categorise and quantify areas of underperformance across wind assets.