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Demand Response Learning.pdf

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Preview of Demand Response Learning
🔗 Source: dcsc.tudelft.nl
📊 Size: 1.32 MB
📄 Pages: 13 pages
⬇️ Downloads: 94

Summary

Residential demand response of thermostatically controlled loads is achieved using batch reinforcement learning, which doesn't require system identification or expert knowledge, making it suitable for large-scale implementation. Batch RL techniques, such as fitted Q-iteration, are extended to incorporate forecasted exogenous data and expert knowledge, and a model-free Monte-Carlo method is proposed to find open-loop schedules for day-ahead markets. Experiments show batch RL provides a valuable alternative to model-based controllers for demand response.

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Description

Residential demand response of thermostatically controlled loads is achieved using batch reinforcement learning, which doesn't require system identification or...

Technical Information

  • File Format: PDF
  • File Size: 1.32 MB
  • Pages: 13
  • Language: EN
  • Total Downloads: 94
  • Last Updated: 7 days ago

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This PDF document about Demand Response Learning provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Demand Response Learning.

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