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Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error

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  • Jie Yang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
    Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Tongyu Liu

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Huaibao Wang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
    Current address: Hebei Avenue 438, Qinhuangdao 066004, China.)

  • Zhenhua Tian

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Shihao Liu

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

Abstract

Thermostatically controlled loads (TCLs) are promising to offer demand-side regulation with proper control. In this paper, the aggregate power of TCLs is used to track the automatic generation control (AGC) signal by changing the temperature setpoint. The dynamics of the indoor temperature are described by a Monte Carlo model, and population dissatisfaction is described by the predicted percentage of dissatisfied (PPD). The objective is optimization from two aspects, minimizing both population dissatisfaction and tracking error. We propose an improved active target particle swarm optimization (APSO) algorithm to optimize the model, making it possible to ensure that the user’s dissatisfaction is as small as possible while the aggregate power tracks the AGC signal. The novelty of this paper is to introduce PPD into the model and at the same time establish three models using PPD as the objective function and constraints. The simulation results are shown to verify the efficiency of the designed model.

Suggested Citation

  • Jie Yang & Tongyu Liu & Huaibao Wang & Zhenhua Tian & Shihao Liu, 2019. "Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error," Energies, MDPI, vol. 12(9), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:9:p:1757-:d:229553
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    References listed on IDEAS

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    1. Zhou, Yue & Wang, Chengshan & Wu, Jianzhong & Wang, Jidong & Cheng, Meng & Li, Gen, 2017. "Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market," Applied Energy, Elsevier, vol. 188(C), pages 456-465.
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    Cited by:

    1. da Fonseca, André L.A. & Chvatal, Karin M.S. & Fernandes, Ricardo A.S., 2021. "Thermal comfort maintenance in demand response programs: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).

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