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Thermodynamic-Based Perceived Predictive Power Control for Renewable Energy Penetrated Resident Microgrids

Author

Listed:
  • Wenhui Shi

    (China Electric Power Research Institute, Beijing 100192, China)

  • Lifei Ma

    (China Electric Power Planning & Engineering Institute, Beijing 100120, China
    School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Wenxin Li

    (Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China)

  • Yankai Zhu

    (School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China)

  • Dongliang Nan

    (Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China)

  • Yinzhang Peng

    (Electric Power Research Institute of State Grid Xinjiang Electric Power Company, Urumqi 830011, China)

Abstract

Heating, ventilation, and air conditioning (HVAC) systems and microgrids have garnered significant attention in recent research, with temperature control and renewable energy integration emerging as key focus areas in urban distribution power systems. This paper proposes a robust predictive temperature control (RPTC) method and a microgrid control strategy incorporating asymmetrical challenges, including uneven power load distribution and uncertainties in renewable outputs. The proposed method leverages a thermodynamics-based R-C model to achieve precise indoor temperature regulation under external disturbances, while a multisource disturbance compensation mechanism enhances system robustness. Additionally, an HVAC load control model is developed to enable real-time dynamic regulation of airflow, facilitating second-level load response and improved renewable energy accommodation. A symmetrical power tracking and voltage support secondary controller is also designed to accurately capture and manage the fluctuating power demands of HVAC systems for supporting operations of distribution power systems. The effectiveness of the proposed method is validated through power electronics simulations in the Matlab/Simulink/SimPowerSystems environment, demonstrating its practical applicability and superior performance.

Suggested Citation

  • Wenhui Shi & Lifei Ma & Wenxin Li & Yankai Zhu & Dongliang Nan & Yinzhang Peng, 2025. "Thermodynamic-Based Perceived Predictive Power Control for Renewable Energy Penetrated Resident Microgrids," Energies, MDPI, vol. 18(12), pages 1-22, June.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:12:p:3027-:d:1673868
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    References listed on IDEAS

    as
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    4. Wu, Jingxuan & Li, Shuting & Fu, Aihui & Cvetković, Miloš & Palensky, Peter & Vasquez, Juan C. & Guerrero, Josep M., 2024. "Hierarchical online energy management for residential microgrids with Hybrid hydrogen–electricity Storage System," Applied Energy, Elsevier, vol. 363(C).
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