/energyplus_rl

Reinforcement Learning testbed + implementations

Primary LanguagePython

Model Based Reinforcement Learning Approach to HVAC optimal control

Repo structure

agent

  • Multi-Objective MDP formulation with objectives as thermal comfort and energy consumption
  • Lagrangian dual reinforcement learning approach
  • fine tuning left to do

mask-agent

  • Single objective MDP of energy consumption, and thermal comfort enforced through hard constraint
  • action bound approach
  • in progress: Inferring change of environment to adjust the mask accordingly

base

  • single objective reinforcement learning formulation (electric cost), with demand response
  • demand response, Toronto Hydro electricity ToU (time of use)
  • To reduce HVAC actuation load, CAPS action smoothing utilized

Algos implemented

  • Rainbow DQN
  • DQN
  • SAC
  • PPO