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Home appliance controller learn from resident negative feedback

Jupyter Notebook 100.00%
demand-response comfort reinforcement-learning

optimization-of-electricity-demand-reduction-with-comfort-conscious-learning's Introduction

Optimization-of-Electricity-Demand-Reduction-with-Comfort-Conscious-Learning

Oral defense slides

Dataset

Smart* Data Set for Sustainability - UMass Smart* Dataset - 2017 release

Datetime encoding

Encoding cyclical continuous features - 24-hour time

Learning Algorithm

Reward Evaluation

Script

  • training.ipynb: take action from PPO and define environment with applianace and resident feedback
  • metrics.ipynb: calculate four evaluation metrics (power, reward, comfort, dr_rate)

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