Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Hierarchical and distributed demand response control strategy for thermostatically controlled appliances in smart grid
Author:
Affiliation:

1. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China; 2. Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada; 3. State Grid Energy Research Institute, Beijing 102209, China

Fund Project:

National High Technology Research and Development Program of China (863 Program) (No. 2015AA050403), National Natural Science Foundation of China (Nos. 51377117, 51407125, 51361135704), China-UK NSFC/EPSRC EV Grant (Nos. 5136113015, EP/L001039/1), ‘‘131’’ Talent and Innovative Team of Tianjin City, State Grid Corporation of China (No. KJ16-1-42), Innovation Leading Talent Project of Qingdao, Shandong Province (No. 15-10-3-15-(43)-zch), and Innovation and Entrepreneurship Development Funds Projects of Qingdao Blue Valley Core Area (No. 201503004).

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    Abstract:

    Thermostatically controlled appliances (TCAs) have great thermal storage capability and are therefore excellent demand response (DR) resources to solve the problem of power fluctuation caused by renewable energy. Traditional centralized management is affected by communication quality severely and thus usually has poor realtime control performance. To tackle this problem, a hierarchical and distributed control strategy for TCAs is established. In the proposed control strategy, target assignment has the feature of self-regulating, owing to the designed target assignment and compensating algorithm which can utilize DR resources maximally in the controlled regions and get better control effects. Besides, the model prediction strategy and customers’ responsive behavior model are integrated into the original optimal temperature regulation (OTR-O), and OTR-O will be evolved into improved optimal temperature regulation. A series of case studies have been given to demonstrate the control effectiveness of the proposed control strategy.

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History
  • Received:
  • Revised:
  • Adopted:
  • Online: January 09,2017
  • Published: