The energy transition and digitalisation are two mega-trends that will affect the world in the coming decades. A planet with more people and rising living standards will need more and cleaner energy solutions. Carbon emissions must be reduced to tackle climate change.

Shell believes that digitalisation and AI are critical enablers to support our ambition to be a net-zero emissions energy business. Shell has been an early adopter of AI, and the use of digital technologies continues to transform Shell’s business, from machine learning to computer vision, deep learning to virtual assistants and autonomous vehicles to robotics. We see great potential in producing renewable power from wind.

The hackathon challenge: windfarm layout optimisation

In this Shell.ai Hackathon for Sustainable and Affordable Energy, we invite you to optimise the placement of 50 wind turbines of ‘100 m rotor diameter each on a hypothetical offshore wind farm area such that the AEP (Annual Energy Production) of the farm is maximized. One of the key problems of an unoptimized layout is the combined effect wind turbines can have on the wind speed distribution in a windfarm. As a wind turbine extracts energy from incoming wind, it creates a region behind it downstream where the wind speed is decreased- this is called a wake region. Note that wind turbines automatically orient their rotors, to face incoming wind from any direction. Due to the induced speed deficit, a turbine placed inside the wake region of an upstream turbine will naturally generate reduced electrical power. This inter-turbine interference is known as a wake effect. An optimal windfarm layout is important to ensure a minimum loss of power during this combined wake effect.

This Shell.ai Hackathon for Sustainable and Affordable Energy edition, focuses on an interesting and complex coding problem. When competing, you will face challenges such as a high dimensionality, complex multimodality and the discontinuous nature of the search space. This makes optimising the layout analytics difficult. But, armed with optimization strategies and computer algorithms, you can solve this problem.

Are you ready to compete, code and win exciting rewards, such as an opportunity to interview for a Shell.ai Residency Programme position in Bangalore?

 

Interested?

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