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A Perspective on Reinforcement Learning in Price-Based Demand Response for Smart Grid
- Authors
- Lu, R.; Hong, S.H.; Zhang, X.; Ye, X.; Song, W.S.
- Issue Date
- Dec-2017
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- Demand response; reinforcement learning; smart grid
- Citation
- Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017, pp.1822 - 1823
- Indexed
- SCOPUS
- Journal Title
- Proceedings - 2017 International Conference on Computational Science and Computational Intelligence, CSCI 2017
- Start Page
- 1822
- End Page
- 1823
- ISSN
- 0000-0000
- Abstract
- This paper proposes a price-based demand response (DR) algorithm for energy management in a hierarchical electricity market. The pricing problem is formulated as a reinforcement learning (RL) model. Using RL, the service provider (SP) can adaptively decide the retail electricity price during the on-line learning process. © 2017 IEEE.
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