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Power-heat coordinated control of multiple energy system for off-grid energy supply using multi-timescale distributed predictive control

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  • Jin, Yuhui
  • Wu, Xiao
  • Shen, Jiong

Abstract

Off-grid multiple energy system (MES) has been regarded as a promising modality for future energy due to high efficiency, consumer adaptability and system independency. Nevertheless, balancing the supply and demand of multiple energy forms simultaneously raises challenges to the operation control due to the strong interactions, characteristic discrepancies and fluctuations among multiple types of energies. The advantages of off-grid MES may never unfold if the multiple energy conversion processes are not managed in a coordinated manner. To this end, this paper takes a typical off-grid combined heat and power generation MES as example to show the strong coupling and multi-timescale features of the MES. A multi-timescale distributed model predictive control (MDMPC) based coordinated controller is then developed to fully exploit the interactions between power and heat, upgrading the operating performance of the MES. Offset free tracking design is also fused in the MDMPC framework to attain more precise following of the load demands even in the presences of process disturbances. Simulation results show that the MDMPC can achieve superior control performance at electricity side while maintaining a high-standard thermal-side control. Discussions are then carried out to further identify the efficacy of the MDMPC under four representative energy consumption scenarios. This paper points to the new directions of using coordinated control strategies for the stable, efficient and flexible operation of modern multiple energy system towards low-carbon transition.

Suggested Citation

  • Jin, Yuhui & Wu, Xiao & Shen, Jiong, 2022. "Power-heat coordinated control of multiple energy system for off-grid energy supply using multi-timescale distributed predictive control," Energy, Elsevier, vol. 254(PB).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s0360544222012397
    DOI: 10.1016/j.energy.2022.124336
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    2. Lu, Nianci & Pan, Lei & Pedersen, Simon & Arabkoohsar, Ahmad, 2023. "A two-dimensional design and synthesis method for coordinated control of flexible-operational combined cycle of gas turbine," Energy, Elsevier, vol. 284(C).
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    6. Deng, Xiangtian & Zhang, Yi & Jiang, Yi & Zhang, Yi & Qi, He, 2024. "A novel operation method for renewable building by combining distributed DC energy system and deep reinforcement learning," Applied Energy, Elsevier, vol. 353(PB).
    7. Lei, Xuanang & Lin, Yujun & Yang, Qiufan & Zhou, Jianyu & Chen, Xia & Wen, Jinyu, 2022. "Research on coordinated control of renewable-energy-based Heat-Power station system," Applied Energy, Elsevier, vol. 324(C).
    8. Zhu, Xiaoxun & Hu, Ming & Xue, Jinfei & Li, Yuxuan & Han, Zhonghe & Gao, Xiaoxia & Wang, Yu & Bao, Linlin, 2024. "Research on multi-time scale integrated energy scheduling optimization considering carbon constraints," Energy, Elsevier, vol. 302(C).
    9. Pang, Simian & Zheng, Zixuan & Xiao, Xianyong & Huang, Chunjun & Zhang, Shu & Li, Jie & Zong, Yi & You, Shi, 2022. "Collaborative power tracking method of diversified thermal loads for optimal demand response: A MILP-Based decomposition algorithm," Applied Energy, Elsevier, vol. 327(C).

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