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Provision of Supplementary Load Frequency Control via Aggregation of Air Conditioning Loads

Author

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  • Lei Zhou

    (Department of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, Jiangsu, China)

  • Yang Li

    (Department of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, Jiangsu, China)

  • Beibei Wang

    (Department of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, Jiangsu, China)

  • Zhe Wang

    (Department of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, Jiangsu, China)

  • Xiaoqing Hu

    (Department of Electrical Engineering, Southeast University, No. 2 Sipailou, Nanjing 210096, Jiangsu, China)

Abstract

The integration of large-scale renewable energy poses great challenges for the operation of power system because of its increased frequency fluctuations. More load frequency control (LFC) resources are demanded in order to maintain a stable system with more renewable energy injected. Unlike the costly LFC resources on generation side, the thermostatically controlled loads (TCLs) on the demand side become an attractive solution on account of its substantial quantities and heat-storage capacity. It generally contains air conditioners (ACs), water heaters and fridges. In this paper, the supplementary LFC is extracted by the modeling and controlling of aggregated ACs. We first present a control framework integrating the supplementary LFC with the traditional LFC. Then, a change-time-priority-list method is proposed to control power output taking into account customers’ satisfaction. Simulations on a single-area power system with wind power integration demonstrate the effectiveness of the proposed method. The impact of ambient temperature changes and customer preferences on room temperature is also involved in the discussion. Results show that the supplementary LFC provided by ACs could closely track the LFC signals and effectively reduce the frequency deviation.

Suggested Citation

  • Lei Zhou & Yang Li & Beibei Wang & Zhe Wang & Xiaoqing Hu, 2015. "Provision of Supplementary Load Frequency Control via Aggregation of Air Conditioning Loads," Energies, MDPI, vol. 8(12), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:12:p:12417-14117:d:60550
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    References listed on IDEAS

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    1. Pedro Faria & Zita Vale & José Baptista, 2015. "Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation," Energies, MDPI, vol. 8(6), pages 1-17, June.
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    3. Rokas Valancius & Andrius Jurelionis & Viktoras Dorosevas, 2013. "Method for Cost-Benefit Analysis of Improved Indoor Climate Conditions and Reduced Energy Consumption in Office Buildings," Energies, MDPI, vol. 6(9), pages 1-16, September.
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    Cited by:

    1. Cheng, Lin & Wan, Yuxiang & Tian, Liting & Zhang, Fang, 2019. "Evaluating energy supply service reliability for commercial air conditioning loads from the distribution network aspect," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    2. Kohlhepp, Peter & Harb, Hassan & Wolisz, Henryk & Waczowicz, Simon & Müller, Dirk & Hagenmeyer, Veit, 2019. "Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 527-547.
    3. Pinto, Rui & Bessa, Ricardo J. & Matos, Manuel A., 2017. "Multi-period flexibility forecast for low voltage prosumers," Energy, Elsevier, vol. 141(C), pages 2251-2263.
    4. Bishnu P. Bhattarai & Kurt S. Myers & Birgitte Bak-Jensen & Sumit Paudyal, 2017. "Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks," Energies, MDPI, vol. 10(1), pages 1-18, January.
    5. Michael Short & Sergio Rodriguez & Richard Charlesworth & Tracey Crosbie & Nashwan Dawood, 2019. "Optimal Dispatch of Aggregated HVAC Units for Demand Response: An Industry 4.0 Approach," Energies, MDPI, vol. 12(22), pages 1-20, November.

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