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Modeling and control of central air conditionings for providing regulation services for power systems

Author

Listed:
  • Xie, Kang
  • Hui, Hongxun
  • Ding, Yi
  • Song, Yonghua
  • Ye, Chengjin
  • Zheng, Wandong
  • Ye, Shuiquan

Abstract

The increasing renewable energies bring more generation fluctuations to power systems, which puts forward a higher requirement on regulation services for maintaining the system balance. Existing traditional generating units probably cannot provide sufficient regulation services to solve this challenge. With the progress of information and communication technologies, it is possible to control demand-side flexible loads to provide regulation services. Among various flexible loads, central air conditionings (CACs) have huge regulation potential, because CACs account for about 40% of the total energy consumption in buildings. However, the operation of CACs is a complicated dynamic process with multiple subsystems and independent control loops. It is difficult to accurately regulate CACs to reach the required regulation services within the comfortable indoor temperature. To address this issue, this paper focuses on the quantitative assessment and two-layer coordinated controls of CACs to provide regulation services for the power system. Firstly, the thermal-electrical model of the CAC is established to describe the dynamic operation process of subsystems’ characteristics. On this basis, a quantitative assessment method of CAC’s regulation services is proposed by discretizing the thermal-electrical operation characteristics. Then, to aggregate multiple CACs to provide significant regulation capacities, an adaptive allocation method is proposed to satisfy the power system’s regulation requirement based on different CACs’ available regulation potential. Furthermore, an online distribution control method is developed to regulate each individual CAC’s cooling capacity for guaranteeing the regulation accuracy and different occupants’ comfortable temperatures. The effectiveness of the proposed models and methods is illustrated by numerical studies.

Suggested Citation

  • Xie, Kang & Hui, Hongxun & Ding, Yi & Song, Yonghua & Ye, Chengjin & Zheng, Wandong & Ye, Shuiquan, 2022. "Modeling and control of central air conditionings for providing regulation services for power systems," Applied Energy, Elsevier, vol. 315(C).
    • Handle: RePEc:eee:appene:v:315:y:2022:i:c:s0306261922004391
    DOI: 10.1016/j.apenergy.2022.119035
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    References listed on IDEAS

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    1. Sensen Deng & Dong Wang & Kangkang Zhang & Mengxue Li & Yuehong Lu, 2024. "Analysis of the Energy-Saving Effect of a Novel Central Air-Conditioning System with an Internal Heat Exchanger in Summer," Sustainability, MDPI, vol. 16(13), pages 1-20, June.
    2. Sun, Yue & Luo, Zhiwen & Li, Yu & Zhao, Tianyi, 2024. "Grey-box model-based demand side management for rooftop PV and air conditioning systems in public buildings using PSO algorithm," Energy, Elsevier, vol. 296(C).
    3. Yang, Shaohua & Lao, Keng-Weng & Hui, Hongxun & Chen, Yulin, 2023. "A robustness-enhanced frequency regulation scheme for power system against multiple cyber and physical emergency events," Applied Energy, Elsevier, vol. 350(C).
    4. Dong, Lianxin & Wu, Qing & Hong, Juhua & Wang, Zhihua & Fan, Shuai & He, Guangyu, 2023. "An adaptive decentralized regulation strategy for the cluster with massive inverter air conditionings," Applied Energy, Elsevier, vol. 330(PA).

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