Machine learning for offshore wind development
- Our mission is to create and sell a Software to offshore wind promotors by Machine Learning.
- This software will predict the best location for floating offshore wind platforms and will also change the design of any particular platform depending on the metoceanic conditions.
Problem & Solution
- Climate Change is the result of Numen act and emissions.
- Wind Energy is the fastest renewable energy growing sector (Cheapest LCOE), however wind onshore
- Offshore wind promotors are facing big challenges to decrease their project coststo become competitive with onshore wind
- High budget for DEVEX& CAPEX of new offshore Projects due to:
- Buoys and testing
- Expensive software to study the behaviour of floating platform under metoceanic conditions. Many hours/engineers.
- 75% of EARTH is WATER
- Offshore wind is exposed to stronger & steadier winds.Increasing 150% the onshore production.
- Until late years, offshore was limited to shallow water zones, but floating will be the new market niche
- We offer a FAST & CHEAPER solution to the floating offshore wind promotors, saving time, resources and money:
- Reduced costs of testing and input of metoceanic data.
- Gather many design and calculation softwares in JUST ONE.
- Machine Learning will save many working hours of data accumulation, calculations and designing.
The technology is based in machine learning where algorithms train a computer to learn and make predictive analysis.
The model obtained for energy prediction gives a very reliable prediction of the energy output for newly supplied weather data and detects patterns
- This concept has been developed rapidly for the last two years with the increase of data and computer processing power.
- It can be applied to many industries worldwide.
- Based on several research on wind in 2014, we can expect at least an optimization of the output of 5 %.
- We can expect the neural networks to learn with the data and optimize the location of the multi turbines floating platform.