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Multi-Objective Decentralized Model Predictive Control for Inverter Air Conditioner Control of Indoor Temperature and Frequency Stabilization in Microgrid

Author

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  • Jonglak Pahasa

    (Department of Electrical Engineering, School of Engineering, University of Phayao, Phayao 56000, Thailand)

  • Potejanasak Potejana

    (Department of Industrial Engineering, School of Engineering, University of Phayao, Phayao 56000, Thailand)

  • Issarachai Ngamroo

    (Department of Electrical Engineering, School of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, Thailand)

Abstract

Microgrid (MG) is a novel concept for a future distribution power system that enables renewable energy sources (RES). The intermittent RES, such as wind turbines and photovoltaic generators, can be connected to the MG via a power electronics inverter. However, the inverter interfaced RESs reduce the total inertia and damping properties of the traditional MG. Consequently, the system exhibits steeper frequency nadir and the rate of change of frequency (RoCoF), which may degrade the dynamic performance and cause the severe frequency fluctuation of the system. Smart loads such as inverter air conditioners (IACs) tend to be used for ancillary services in power systems. The power consumption of IACs can be regulated to suppress frequency fluctuation. Nevertheless, these IACs, regulating power, can cause the deviation of indoor temperature from the temperature setting. The variation in indoor temperature should be controlled to fulfill residential comfort. This paper proposes a multi-objective decentralized model predictive control (DMPC) for controlling the power consumption of IACs to reduce MG frequency fluctuation and control the variation in indoor temperature. Simulation results on the studied microgrid with the high penetration of wind and photovoltaic generator demonstrate that the proposed DMPC is able to regulate frequency deviation and control indoor temperature deviation as a user preference. In addition, the DMPC has a superior performance effect to the proportional-integral (PI) controller in terms of reducing frequency deviation, satisfying indoor temperature preferences, and being robust to the varying numbers of IACs.

Suggested Citation

  • Jonglak Pahasa & Potejanasak Potejana & Issarachai Ngamroo, 2021. "Multi-Objective Decentralized Model Predictive Control for Inverter Air Conditioner Control of Indoor Temperature and Frequency Stabilization in Microgrid," Energies, MDPI, vol. 14(21), pages 1-22, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:6969-:d:663378
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    References listed on IDEAS

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    1. Shiyao Qin & Yuyang Chang & Zhen Xie & Shaolin Li, 2021. "Improved Virtual Inertia of PMSG-Based Wind Turbines Based on Multi-Objective Model-Predictive Control," Energies, MDPI, vol. 14(12), pages 1-20, June.
    2. Sandro Sitompul & Goro Fujita, 2021. "Impact of Advanced Load-Frequency Control on Optimal Size of Battery Energy Storage in Islanded Microgrid System," Energies, MDPI, vol. 14(8), pages 1-18, April.
    3. Hui, Hongxun & Ding, Yi & Liu, Weidong & Lin, You & Song, Yonghua, 2017. "Operating reserve evaluation of aggregated air conditioners," Applied Energy, Elsevier, vol. 196(C), pages 218-228.
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    Cited by:

    1. Tetsushi Ono & Aya Hagishima & Jun Tanimoto, 2022. "Non-Intrusive Detection of Occupants’ On/Off Behaviours of Residential Air Conditioning," Sustainability, MDPI, vol. 14(22), pages 1-20, November.

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