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Order reduction method for high-order dynamic analysis of heterogeneous integrated energy systems

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  • Wang, L.X.
  • Zheng, J.H.
  • Li, Z.G.
  • Jing, Z.X.
  • Wu, Q.H.

Abstract

The dynamics of heterogeneous integrated energy systems (HIES) coupling of electricity, gas, and heating/cooling subsystems is with high-order characteristics. The complex dynamics, including electromagnetic transients, electromechanical transients, hydraulic and thermal dynamics, exist in different system devices and interacts with others in different time scales. To deal with the difficulty of analysing the multi-time scale dynamics, this paper proposes an order reduction method (ORM) to map high-order modes into a lower dimensional space. Firstly, the complex model of HIES is partitioned and modelled by individuals, and the dynamic characteristics of each unit is revealed. Then modal synthesis is used to obtain feature modes of the system. Similar dynamics of individuals are synthesized whereas different modes are classified in order. When exploring dynamic process of a certain variable, the relevant modes are extracted from the synthesis model, with other modes handled as parametric or algebraic equations. Simulation studies are conducted to investigate dynamic characteristics of a test HIES using the proposed ORM. The results indicate that the proposed method is capable of simulating high-order dynamics of the test system. Furthermore, it has advantages in both computation accuracy and time, compared with equal-step method and conventional subsystem multi-step simulation method.

Suggested Citation

  • Wang, L.X. & Zheng, J.H. & Li, Z.G. & Jing, Z.X. & Wu, Q.H., 2022. "Order reduction method for high-order dynamic analysis of heterogeneous integrated energy systems," Applied Energy, Elsevier, vol. 308(C).
    • Handle: RePEc:eee:appene:v:308:y:2022:i:c:s0306261921015269
    DOI: 10.1016/j.apenergy.2021.118265
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    References listed on IDEAS

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    1. Zhang, Tong & Li, Zhigang & Wu, Q.H. & Zhou, Xiaoxin, 2019. "Decentralized state estimation of combined heat and power systems using the asynchronous alternating direction method of multipliers," Applied Energy, Elsevier, vol. 248(C), pages 600-613.
    2. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    3. Zheng, J.H. & Wu, Q.H. & Jing, Z.X., 2017. "Coordinated scheduling strategy to optimize conflicting benefits for daily operation of integrated electricity and gas networks," Applied Energy, Elsevier, vol. 192(C), pages 370-381.
    4. Pan, Zhaoguang & Guo, Qinglai & Sun, Hongbin, 2016. "Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow," Applied Energy, Elsevier, vol. 167(C), pages 230-243.
    5. Wang, Lixiao & Jing, Z.X. & Zheng, J.H. & Wu, Q.H. & Wei, Feng, 2018. "Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals," Energy, Elsevier, vol. 158(C), pages 607-622.
    6. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
    7. Berjawi, A.E.H. & Walker, S.L. & Patsios, C. & Hosseini, S.H.R., 2021. "An evaluation framework for future integrated energy systems: A whole energy systems approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
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    Cited by:

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