cs238-windfarm

Final Project -- Optimizing Wind Turbine Placement Subject to Turbine Wakes

This is the code for the Final Project of the CS238: Decision Making Under Uncertainty course at Stanford University (https://web.stanford.edu/class/aa228/cgi-bin/wp/) in Autumn '21. For this project, I collaborated with Yu Shen Lu and Peiyun Zhu.

We optimized wind turbine placement in a wind farm, subject to wake effects, using Q-learning. I worked especially on utilizing Q-learning in conjunction with Neural Networks to estimate the Q-values of unvisited states.

You can access the full paper describing our approach and results at https://drive.google.com/file/d/1C7j7oJPxmxfU-xEoCAaACzxqGy0f2Osk/view.

Our paper was also added to the course website: https://web.stanford.edu/class/aa228/cgi-bin/wp/old-projects/.