In this hackathon, the challenge is to optimize the placement of Nturb , 50 wind turbines of 100 m rotor diameter and 100 m height each on a hypothetical 2D offshore wind farm area such that the AEP (Annual Energy Production) of the farm is maximized. The farm area for this problem is square in shape having dimensions: length Lx = 4 km, width Ly = 4 km. The orientation of farm is such that one of its edges is parallel to the geographical North direction. See Figure 1. There it can be assumed that the positive y and x axis shown are aligned with the geographical North and East directions respectively. There are two constraints that must not be violated by a wind farm layout to be con- sidered valid.

• Perimeter Constraint. All the turbines must be located inside the perimeter of the farm, while maintaining a minimum clearance of 50 meters from the farm boundary.
• Proximity Constraint. The distance between any two turbines must be larger than a given security threshold to ensure a longer lifetime of the turbine rotors. This minimum distance between two turbines is called Dmin and needs to be 400 m.






Shell.ai Hackathon Windfarm Layout Optimisation (WFLO) Challenge

TEAM MEMBERS

• Awanit Ranjan (Team Leader)
• Akash Hemantrao Waitage
• Abhishek Choudhary
• Vivek Kumar








I am glad to state that our Team named as TEAM-7 won the fourth position on Leader Board and First Position under Special University Edition(SPE) from South Zone with the score of 544.70305 .

Here is the list of Teams Won


LEADERBOARD




The Approach/Algorithm which we used for solving WFLOP is in Folder named as Approach. :))




• If you are excited to see the videos of our work check the links below :

  • Pitch Video : https://youtu.be/_ahxVd1lSmY