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Distributed aggregation control of grid-interactive smart buildings for power system frequency support

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  • Wang, Yu
  • Xu, Yan
  • Tang, Yi

Abstract

Grid-interactive smart buildings with thermostatically-controlled loads can be modeled as virtual energy storage systems with dissipation, which have great potentials for providing grid ancillary services such as frequency support. In this paper, a new distributed aggregation control method is proposed for multiple grid-interactive smart buildings in one frequency control area (e.g. a residential community) to provide fast frequency support. The proposed method is based on the distributed sliding mode control via a leader-follower communication scheme. A leader control is designed to provide power and comfort/energy level references for the smart building aggregator based on the area frequency deviation, while references are tracked by each smart building using the proposed distributed sliding mode control. The stability of the proposed control method for grid-interactive smart buildings is proved by the Lyapunov method. With the proposed method, the external characteristics of the aggregated smart buildings will have good power tracking and energy recovery capability, which can effectively improve the system frequency response. In the aggregator, fair and efficient power and comfort/energy level sharing are achieved among all participating grid-interactive smart buildings. The proposed control scheme is tested on a three-area power system considering both system contingency and normal operation scenarios.

Suggested Citation

  • Wang, Yu & Xu, Yan & Tang, Yi, 2019. "Distributed aggregation control of grid-interactive smart buildings for power system frequency support," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
  • Handle: RePEc:eee:appene:v:251:y:2019:i:c:54
    DOI: 10.1016/j.apenergy.2019.113371
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    References listed on IDEAS

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    Cited by:

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    2. Li, Zhihao & Yang, Lun & Xu, Yinliang, 2023. "A dynamics-constrained method for distributed frequency regulation in low-inertia power systems," Applied Energy, Elsevier, vol. 344(C).
    3. Chu Donatus Iweh & Samuel Gyamfi & Emmanuel Tanyi & Eric Effah-Donyina, 2021. "Distributed Generation and Renewable Energy Integration into the Grid: Prerequisites, Push Factors, Practical Options, Issues and Merits," Energies, MDPI, vol. 14(17), pages 1-34, August.
    4. Saman Nikkhah & Adib Allahham & Janusz W. Bialek & Sara L. Walker & Damian Giaouris & Simira Papadopoulou, 2021. "Active Participation of Buildings in the Energy Networks: Dynamic/Operational Models and Control Challenges," Energies, MDPI, vol. 14(21), pages 1-28, November.
    5. Mahsa Khorram & Pedro Faria & Zita Vale & Carlos Ramos, 2020. "Sequential Tasks Shifting for Participation in Demand Response Programs," Energies, MDPI, vol. 13(18), pages 1-16, September.
    6. Rehman, Obaid Ur & Khan, Shahid A. & Javaid, Nadeem, 2021. "Decoupled building-to-transmission-network for frequency support in PV systems dominated grid," Renewable Energy, Elsevier, vol. 178(C), pages 930-945.
    7. Wenya Xu & Yanxue Li & Guanjie He & Yang Xu & Weijun Gao, 2023. "Performance Assessment and Comparative Analysis of Photovoltaic-Battery System Scheduling in an Existing Zero-Energy House Based on Reinforcement Learning Control," Energies, MDPI, vol. 16(13), pages 1-19, June.

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