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A Closed-Loop Control Strategy for Air Conditioning Loads to Participate in Demand Response

Author

Listed:
  • Xiaoqing Hu

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Beibei Wang

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, China
    These authors contributed equally to this work.)

  • Shengchun Yang

    (China Electric Power Research Institute, Nanjing 210003, China
    These authors contributed equally to this work.)

  • Taylor Short

    (Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, TN 37996, USA
    These authors contributed equally to this work.)

  • Lei Zhou

    (Department of Electrical Engineering, Southeast University, Nanjing 210096, China
    These authors contributed equally to this work.)

Abstract

Thermostatically controlled loads (TCLs), such as air conditioners (ACs), are important demand response resources—they have a certain heat storage capacity. A change in the operating status of an air conditioner in a small range will not noticeably affect the users’ comfort level. Load control of TCLs is considered to be equivalent to a power plant of the same capacity in effect, and it can significantly reduce the system pressure to peak load shift. The thermodynamic model of air conditioning can be used to study the aggregate power of a number of ACs that respond to the step signal of a temperature set point. This paper analyzes the influence of the parameters of each AC in the group to the indoor temperature and the total load, and derives a simplified control model based on the two order linear time invariant transfer function. Then, the stability of the model and designs its Proportional-Integral-Differential (PID) controller based on the particle swarm optimization (PSO) algorithm is also studied. The case study presented in this paper simulates both scenarios of constant ambient temperature and changing ambient temperature to verify the proposed transfer function model and control strategy can closely track the reference peak load shifting curves. The study also demonstrates minimal changes in the indoor temperature and the users’ comfort level.

Suggested Citation

  • Xiaoqing Hu & Beibei Wang & Shengchun Yang & Taylor Short & Lei Zhou, 2015. "A Closed-Loop Control Strategy for Air Conditioning Loads to Participate in Demand Response," Energies, MDPI, vol. 8(8), pages 1-32, August.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:8:p:8650-8681:d:54217
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    References listed on IDEAS

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    Cited by:

    1. Tanima Bal & Saheli Ray & Nidul Sinha & Ramesh Devarapalli & Łukasz Knypiński, 2023. "Integrating Demand Response for Enhanced Load Frequency Control in Micro-Grids with Heating, Ventilation and Air-Conditioning Systems," Energies, MDPI, vol. 16(15), pages 1-23, August.
    2. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    3. Valeria Palomba & Efstratios Varvagiannis & Sotirios Karellas & Andrea Frazzica, 2019. "Hybrid Adsorption-Compression Systems for Air Conditioning in Efficient Buildings: Design through Validated Dynamic Models," Energies, MDPI, vol. 12(6), pages 1-28, March.

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