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A Novel Grid Load Management Technique using Electric Water Heaters and Q-learning
Proceedings of the 2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014
  • Khalid Al-Jabery
  • Donald C. Wunsch, Missouri University of Science and Technology
  • Jinjun Xiong
  • Yiyu Shi, Missouri University of Science and Technology
Abstract

This paper describes a novel technique for controlling demand-side management (DSM) by optimizing the power consumed by Domestic Electric Water Heaters (DEWH) while maintaining customer satisfaction. The system has 18 states based on three factors: instantaneous grid load, water consumption, and the temperature of the water supplied. The current state of the system is defined based on its fuzzy membership for each factor. The resulting model represents a Semi-Markov decision process (SMDP) with two possible actions, 'On' and 'Off.' Rewards are assigned for each action-state pairs proportionally to the fuzzy membership of the system in the new state. A simulation study was conducted to compare the proposed method with three previous approaches. The proposed method demonstrated better performance in reducing the overall grid power demand and flattening its peaks. Furthermore, it provides better rate of customers' satisfaction than the uncontrolled operation.

Meeting Name
2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014 (2014: Nov. 3-6, Venice, Italy)
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
International Standard Book Number (ISBN)
978-1479949342
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
1-1-2015
Publication Date
01 Jan 2015
Citation Information
Khalid Al-Jabery, Donald C. Wunsch, Jinjun Xiong and Yiyu Shi. "A Novel Grid Load Management Technique using Electric Water Heaters and Q-learning" Proceedings of the 2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014 (2015) p. 776 - 781
Available at: http://works.bepress.com/donald-wunsch/3/