jingzhountu / real-time-turbine-angle-optimization-using-rl-based-algorithms

The objective of this project is to optimize the angle of a turbine in real-time to maximize energy production while minimizing rotation costs. This is achieved by employing reinforcement learning (RL) based algorithms.

wind_turbine_env

Working environment to simulate the power output of a wind turbine given a simulation of the wind

Packages requirements

numpy, scipy and matlplotlib

Environment

Wind

The wind has a short term variation from the Ornstein-Uhlenbeck and a long term variation with a period of 24h. The short term variation are here to simulate events like wind gusts whereas the long term variation corresponds to diurnal cycles.

Wind turbine

The wind turbine corresponds to a Vestas V80 machine. It outputs power for a given wind and wind angle. Its sensor reading is not perfect, it has a little constant bias.

The turbine heading can be moved clockwise, trigo or remain the same. Each action that modifies the angle costs some power that penalizes the output.

Basic agent

A very simple agent that will tell the wind turbine to follow the wind when their relative angle becomes too big

Simu

It allows to glue together the different structures and to run a simulation for a given duration. An exemple of how this can work together is given in the demo.py file