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Machine Learning (ML) can already use weather data to monitor turbine blades' location and determine how much energy they produce or prevent damage to high winds or storms.
FREMONT, CA: Since the beginning of the decade, wind energy has grown steadily worldwide, with the amount of energy produced by offshore wind rising by almost 30 percent each year. Countries worldwide need to quickly maximize their supply of renewable energy to satisfy increasing demand and reduce emissions rapidly. Despite this urgency, offshore wind supplies less than one percent of the world's energy supply.
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The explanation for this untapped capacity is that 80 percent of wind blows uninterrupted further offshore more than 60 meters deep in water, where turbines embedded in the seafloor are challenging to build.
But recent projects, show that it is possible to build floating wind turbines. A single six-megawatt turbine can generate enough electricity to power 4,000 homes. Unfortunately, while floating wind farms are technically feasible, they are not economically viable. Doing anything offshore is expensive.
Technological Solutions
Thus, new technologies are likely to be required to make floating wind farms cost-effective. For example, using robots and other autonomous technology to monitor offshore engineering operations from seabed investigations to operating, monitoring, and maintaining a floating wind turbine may minimize staff risk and provide more efficient control of these complex systems.
Routine inspections of offshore wind farms will be impractical to the large projects being constructed today and certainly to those expected for the future. Smart sensors installed into all parts of a floating wind farm will continuously determine how the system functions instead. Machine learning, which uses data to teach computers to make decisions on their own, may be used to tell us the most effective anchor during design or whether a mooring line could be at risk of failure during service.
Machine Learning (ML) can already use weather data to monitor turbine blades' location and determine how much energy they produce or prevent damage to high winds or storms. New approaches integrating physics with ML can make accurate predictions with less useful offshore information, where data can be challenging to gather.
As the governments launch an investigation into technical developments that could solve climate change, offshore wind is the first port of call. By investing in future technologies, floating wind farms could improve a country's and the world's renewable energy potential.
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