policy
PPO-9-turbine-case
AkhilP35 · PyTorch
or hover any field below to flag it
Overview
Name
PPO-9-turbine-case
Author
AkhilP35
Framework
PyTorch
License
unknown
Skill type
other
Evidence level
untested
Task description
This project trains a Proximal Policy Optimization (PPO) agent to control yaw angles in a 9‑turbine wind farm using the WFSim MATLAB simulator. It provides a Python reinforcement learning workflow that interfaces with MATLAB via the Engine API to optimize wind farm power output.
Spaces
Action space
other · 0-dim · 0Hz
Observation space
- type: other
Links
HuggingFace repo
null
Paper (arXiv)
null
Compatible robots
3+17 mentioned but not in catalog yetCompatible environments
0No environments list PPO-9-turbine-case yet.
Datasets that reference this policy
0No datasets reference PPO-9-turbine-case yet.