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Grid-Following Inverter-Based Resource: Numerical State–Space Modeling

Author

Listed:
  • Abdullah Alassaf

    (Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55211, Saudi Arabia)

  • Ibrahim Alsaleh

    (Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55211, Saudi Arabia)

  • Ayoob Alateeq

    (Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55211, Saudi Arabia)

  • Hamoud Alafnan

    (Department of Electrical Engineering, College of Engineering, University of Hail, Hail 55211, Saudi Arabia)

Abstract

In the pursuit of a sustainable electric power system, the integration of renewable energy sources and distributed energy resources is gradually replacing traditional power generation. These new resources are integrated into the grid via inverters, which, despite their efficient performance, present dynamic challenges to the power grid when implemented on a large scale. To maintain grid stability and ensure effective regulation during abnormal operations, various modeling techniques are necessary; while the dynamics of inverter-based resources (IBRs) are traditionally modeled by transfer functions, this paper sheds light on differential-algebraic equations (DAEs) modeling and numerical integration methods. The inherent limitations of transfer function modeling stem from its restricted applicability, as it is exclusively suitable for linear and time-invariant systems. In contrast, the nonlinear DAEs of the IBR system can be converted into a state–space form, which offers a versatile framework for modeling, evaluating, and designing a diverse array of systems. In addition to being compatible with time-varying systems and multiple-input multiple-output systems, the state–space technique may incorporate saturation and dead zone characteristics into the dynamic model. Our research focuses on IBR modeling in a grid-following scheme, which is current-controlled and synchronized to the grid by a phase-locked loop (PLL). The presented state–space model consists of the inverter, grid, control, and designed PLL. Beyond the discussion of its application to IBRs, the presented method holds the potential to solve a wide range of DAEs. The proposed model is compared with a benchmarked system.

Suggested Citation

  • Abdullah Alassaf & Ibrahim Alsaleh & Ayoob Alateeq & Hamoud Alafnan, 2023. "Grid-Following Inverter-Based Resource: Numerical State–Space Modeling," Sustainability, MDPI, vol. 15(10), pages 1-18, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:10:p:8400-:d:1152745
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    References listed on IDEAS

    as
    1. Pepermans, G. & Driesen, J. & Haeseldonckx, D. & Belmans, R. & D'haeseleer, W., 2005. "Distributed generation: definition, benefits and issues," Energy Policy, Elsevier, vol. 33(6), pages 787-798, April.
    2. Yijia Cao & Jiaqi Yu & Yong Xu & Yong Li & Jingrong Yu, 2017. "An Efficient Phase-Locked Loop for Distorted Three-Phase Systems," Energies, MDPI, vol. 10(3), pages 1-16, February.
    3. Filip Filipović & Milutin Petronijević & Nebojša Mitrović & Bojan Banković & Vojkan Kostić, 2019. "A Novel Repetitive Control Enhanced Phase-Locked Loop for Synchronization of Three-Phase Grid-Connected Converters," Energies, MDPI, vol. 13(1), pages 1-25, December.
    4. Mansoor Alturki & Rabeh Abbassi & Abdullah Albaker & Houssem Jerbi, 2022. "A New Hybrid Synchronization PLL Scheme for Interconnecting Renewable Energy Sources to an Abnormal Electric Grid," Mathematics, MDPI, vol. 10(7), pages 1-21, March.
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