Offshore wind can greatly reduce operations and maintenance costs and increase power output with a better understanding of asset performance
Until the offshore wind industry uses its data effectively to quantify the impact of offshore conditions over turbine lifetime, offshore wind will continue to face high operational costs, miss initially modelled power output capacity, and as a consequence suffer increased financing costs.
This is, at least, according to Clir Renewables, the leading provider of digital asset performance technology for wind energy, which supports over 5 GW of assets worldwide. Clir analyzes wind turbine data via artificial intelligence in order to identify causes of underperformance, informing asset owners and operators of strategies they can take to improve performance and thereby increase annual energy production by up to 5%.
The offshore wind industry is credited as the principle way forward for utility-scale renewable energy across many markets, and is set to expand up to 70 GW to account for 9.9% of Europe’s electricity needs by 2030. However, this growth continues to be accompanied by a proliferation of ‘operational unknowns’ that risk this target being missed.
Indeed, as recent financial results from major offshore wind operators have demonstrated, revenues may be pushed downwards by risks that in Clir Renewables’ opinion were predictable. If offshore wind technology is to be effectively capitalized upon in the future, it is important that owners and operators are investing in technologies that provide a more granular understanding of operational performance and feeding back lessons learned.
“Larger turbine designs and the stratified atmosphere found in offshore wind have pushed the demands facing this technology to greater heights than ever before,” commented Gareth Brown, Chief Executive Officer, Clir. “Clarifying the effect of the harsh offshore conditions on new turbines, however, still remains a challenge for the industry.”
“We know, for example, that capacity expectations have been developed optimistically, as you can’t take underperformance into account if you rely on old design assumptions which don’t cover the performance issues new offshore turbines, such as atmospheric stability that drives wake effects and the blockage effect. Focusing on these unknowns is key to informing financial decisions for future expansion of the industry.”
“Artificial Intelligence, and its proliferation into renewables, is an essential tool to answer many of these questions, but its integration must be based on deep domain expertise applied and built with transparency from all stakeholders. Only then, can we take a further look at performance, drive new cost efficiencies in operational projects and feedback into new development assets.”
“Ultimately, having a complete picture of asset performance will be absolutely crucial to the continued growth of offshore wind.”
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