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Energy-efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system

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  • Mei, Jun
  • Xia, Xiaohua

Abstract

Generally, conventional controllers for comfort are designed by using on/off control or proportional-integral (PI) control, with little consideration of energy consumption of the system. This paper presents a multi-input-multi-output (MIMO) model predictive control (MPC) for a direct expansion (DX) air conditioning (A/C) system to improve both indoor thermal comfort and air quality, whereas the energy consumption is minimised. The DX A/C system is modelled into a nonlinear system, with a varying speed of compressor and varying speed of supply fan and volume flow rate of supply air being regarded as inputs. We first propose an open loop controller based on an optimisation of energy consumption with the advantage of a unique set of steady states. The MPC controller is proposed to optimise the transient processes reaching the steady state. To facilitate the MPC design, the nonlinear model is linearised around its steady state. MPC is designed for the linearised model. The advantages of the proposed energy-optimised open loop controller and the closed-loop regulation of the MIMO MPC scheme are verified by simulation results.

Suggested Citation

  • Mei, Jun & Xia, Xiaohua, 2017. "Energy-efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system," Applied Energy, Elsevier, vol. 195(C), pages 439-452.
  • Handle: RePEc:eee:appene:v:195:y:2017:i:c:p:439-452
    DOI: 10.1016/j.apenergy.2017.03.076
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    References listed on IDEAS

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    1. Wanjiru, Evan M. & Zhang, Lijun & Xia, Xiaohua, 2016. "Model predictive control strategy of energy-water management in urban households," Applied Energy, Elsevier, vol. 179(C), pages 821-831.
    2. Wu, Zhou & Wang, Bo & Xia, Xiaohua, 2016. "Large-scale building energy efficiency retrofit: Concept, model and control," Energy, Elsevier, vol. 109(C), pages 456-465.
    3. Tu, Rang & Liu, Xiao-Hua & Jiang, Yi, 2015. "Irreversible processes and performance improvement of desiccant wheel dehumidification and cooling systems using exergy," Applied Energy, Elsevier, vol. 145(C), pages 331-344.
    4. Carstens, Herman & Xia, Xiaohua & Ye, Xianming, 2014. "Improvements to longitudinal Clean Development Mechanism sampling designs for lighting retrofit projects," Applied Energy, Elsevier, vol. 126(C), pages 256-265.
    5. Wu, Zhou & Tazvinga, Henerica & Xia, Xiaohua, 2015. "Demand side management of photovoltaic-battery hybrid system," Applied Energy, Elsevier, vol. 148(C), pages 294-304.
    6. Wang, Nan & Zhang, Jiangfeng & Xia, Xiaohua, 2013. "Desiccant wheel thermal performance modeling for indoor humidity optimal control," Applied Energy, Elsevier, vol. 112(C), pages 999-1005.
    7. Wanjiru, Evan M. & Xia, Xiaohua, 2015. "Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation," Applied Energy, Elsevier, vol. 160(C), pages 521-531.
    8. Li, Ning & Xia, Liang & Shiming, Deng & Xu, Xiangguo & Chan, Ming-Yin, 2012. "Dynamic modeling and control of a direct expansion air conditioning system using artificial neural network," Applied Energy, Elsevier, vol. 91(1), pages 290-300.
    9. Fan, Yuling & Xia, Xiaohua, 2017. "A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance," Applied Energy, Elsevier, vol. 189(C), pages 327-335.
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