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Improving photovoltaic self-consumption and building power generation-consumption matching via indoor humidity flexible control

Author

Listed:
  • Liu, Shuo
  • Xue, Zhifeng
  • Zhang, Yongjie
  • Zhang, Tao
  • Liu, Xiaohua
  • Wang, Chaoliang
  • Liu, Wei

Abstract

As the demand for energy efficiency and renewable energy integration in buildings increases, optimizing the matching between electricity consumption and photovoltaic (PV) generation becomes crucial. This study investigates the integration of the temperature and humidity independent control (THIC) system as a flexible resource with energy storage (ES) systems to improve the matching performance. The research evaluates the impact of different flexible control strategies on the energy consumption pattern, electricity cost, and feed-in electricity. Results show that the THIC system with S1 (temperature-based) and S2 (temperature and humidity-based) flexible control strategies improve the self-consumption rate (SCR) by 12 % and 21 %, and the self-sufficiency rate (SSR) by 14.7 % and 22.5 %, respectively, compared to the general control scenario. Flexible control on indoor humidity improves matching performance by a further 28 %. The study further analyzes the combined effects of the THIC system and ES strategies, showing that the integration of the S2 strategy with various ES strategies improves SCR and SSR while reducing feed-in electricity and electricity costs, yet highlights the need for synergy. The findings provide valuable insights for increasing the utilization of renewable energy in buildings, contributing to more sustainable and cost-effective building energy management solutions.

Suggested Citation

  • Liu, Shuo & Xue, Zhifeng & Zhang, Yongjie & Zhang, Tao & Liu, Xiaohua & Wang, Chaoliang & Liu, Wei, 2026. "Improving photovoltaic self-consumption and building power generation-consumption matching via indoor humidity flexible control," Renewable Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:renene:v:258:y:2026:i:c:s0960148125025686
    DOI: 10.1016/j.renene.2025.124904
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    References listed on IDEAS

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    1. Liu, Shuo & Liu, Xiaohua & Zhang, Tao & Wang, Chaoliang & Liu, Wei, 2024. "Joint optimization for temperature and humidity independent control system based on multi-agent reinforcement learning with cooperative mechanisms," Applied Energy, Elsevier, vol. 375(C).
    2. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
    3. Liu, Shuo & Jang, Hyusan & Yeo, Myoung-Souk, 2023. "Experimental study on the operating characteristic of the desiccant cooling systems with the potential of condensing heat recovery," Energy, Elsevier, vol. 283(C).
    4. Zou, Bin & Peng, Jinqing & Li, Sihui & Li, Yi & Yan, Jinyue & Yang, Hongxing, 2022. "Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings," Applied Energy, Elsevier, vol. 305(C).
    5. Zou, Bin & Peng, Jinqing & Yin, Rongxin & Li, Houpei & Li, Sihui & Yan, Jinyue & Yang, Hongxing, 2022. "Capacity configuration of distributed photovoltaic and battery system for office buildings considering uncertainties," Applied Energy, Elsevier, vol. 319(C).
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