Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Rolling horizon optimization for real-time operation of thermostatically controlled load aggregator
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Affiliation:

1 School of Civil Engineering, University of Sydney, Sydney, Australia 2 State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing, China 3 School of Electrical and Information Engineering, University of Sydney, Sydney, Australia

Fund Project:

This work was supported in part by the Australian Research Council through its Future Fellowship scheme (No. FT140100130), in part by the Visiting Scholarship of State Key Laboratory of Power Transmission Equipment & System Security and New Technology (Chongqing University, China) (No. 2007DA10512716401), and in part by the Early Career Research Development Scheme of Faculty of Engineering and Information Technology, University of Sydney, Australia. The authors also would like to acknowledge Dr. Yingying CHEN from The University of Sydney for her valuable assistance on the independent format checking of this paper.

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    Abstract:

    Thermostatically controlled loads (TCLs) have great potentials to participate in the demand response programs due to their flexibility in storing thermal energy. The two-way communication infrastructure of smart grids provides opportunities for the smart buildings/houses equipped with TCLs to be aggregated in their participation in the electricity markets. This paper focuses on the realtime scheduling of TCL aggregators in the power market using the structure of the Nordic electricity markets a case study. An International Organization of Standardization (ISO) thermal comfort model is employed to well control the occupants’ thermal comfort, while a rolling horizon optimization (RHO) strategy is proposed for the TCL aggregator to maximize its profit in the regulation market and to mitigate the impacts of system uncertainties. The simulations are performed by means of a metaheuristic optimization algorithm, i.e., natural aggregation algorithm (NAA). A series of simulations are conducted to validate the effectiveness of proposed method.

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History
  • Received:
  • Revised:
  • Adopted:
  • Online: November 27,2017
  • Published: