Trajectory tracking with an aggregation of domestic hot water heaters: Combining model-based and model-free control in a commercial deployment
Abstract
Scalable demand response of residential electric loads has been a timely research topic in recent years. The commercial coming of age or residential demand response requires a scalable control architecture that is both efficient and practical to use. This work presents such a strategy for domestic hot water heaters and present a commercial proof-of-concept deployment. The strategy combines state of the art in aggregate-and-dispatch with a novel dispatch strategy leveraging recent developments in reinforcement learning and is tested in a hardware-in-the-loop simulation environment. The results are promising and present how model-based and model-free control strategies can be merged to obtain a mature and commercially viable control strategy for residential demand response.
- Publication:
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arXiv e-prints
- Pub Date:
- May 2018
- DOI:
- 10.48550/arXiv.1805.04228
- arXiv:
- arXiv:1805.04228
- Bibcode:
- 2018arXiv180504228L
- Keywords:
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- Mathematics - Optimization and Control
- E-Print:
- 8 pages, 8 figures, submitted to IEEE Transactions on Smart Grid