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Double Deep Q-Networks for Optimizing Electricity Cost of a Water Heater...

Publication Type
Conference Paper
Book Title
2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Publication Date
Page Numbers
1 to 5
Conference Name
Innovative Smart Grid Technologies (ISGT 2021)
Conference Location
Washington, District of Columbia, United States of America
Conference Sponsor
IEEE
Conference Date
-

Electric water heaters represent 14% of the electricity consumption in the residential buildings and the cost associated with domestic water heating account for a good portion of the household expenses in the United States. In this context, intelligent control of water heaters gained a lot of research attention. In recent years, a significant number of intelligent water heater controllers, with various methods and intended uses, have been proposed. However, existing studies are mostly model-based approaches that require an accurate modelling of the water heater. Towards addressing this research gap, this paper presents a model-free reinforcement learning-based controller for a day-ahead price market. The controller aims to minimize the cost of domestic water heating while maintaining the user comfort. The results showed that the developed controller can help save energy cost while maintaining the temperatures within the desired comfort band.