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General Dynamic Equivalent Modeling of Microgrid Based on Physical Background

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  • Changchun Cai

    (Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology, Hohai University, Changzhou 213022, Jiangsu, China
    College of IOT Engineering, Hohai University, Changzhou 213022, Jiangsu, China
    Changzhou Key Laboratory of Photovoltaic System Integration and Production Equipment, Hohai University, Changzhou 213022, Jiangsu, China)

  • Bing Jiang

    (Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology, Hohai University, Changzhou 213022, Jiangsu, China
    College of IOT Engineering, Hohai University, Changzhou 213022, Jiangsu, China)

  • Lihua Deng

    (Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology, Hohai University, Changzhou 213022, Jiangsu, China
    College of IOT Engineering, Hohai University, Changzhou 213022, Jiangsu, China)

Abstract

Microgrid is a new power system concept consisting of small-scale distributed energy resources; storage devices and loads. It is necessary to employ a simplified model of microgrid in the simulation of a distribution network integrating large-scale microgrids. Based on the detailed model of the components, an equivalent model of microgrid is proposed in this paper. The equivalent model comprises two parts: namely, equivalent machine component and equivalent static component. Equivalent machine component describes the dynamics of synchronous generator, asynchronous wind turbine and induction motor, equivalent static component describes the dynamics of photovoltaic, storage and static load. The trajectory sensitivities of the equivalent model parameters with respect to the output variables are analyzed. The key parameters that play important roles in the dynamics of the output variables of the equivalent model are identified and included in further parameter estimation. Particle Swarm Optimization (PSO) is improved for the parameter estimation of the equivalent model. Simulations are performed in different microgrid operation conditions to evaluate the effectiveness of the equivalent model of microgrid.

Suggested Citation

  • Changchun Cai & Bing Jiang & Lihua Deng, 2015. "General Dynamic Equivalent Modeling of Microgrid Based on Physical Background," Energies, MDPI, vol. 8(11), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:11:p:12354-12948:d:58927
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    References listed on IDEAS

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    1. Chuanwen, Jiang & Bompard, Etorre, 2005. "A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(1), pages 57-65.
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    Cited by:

    1. Liuming Jing & Dae-Hee Son & Sang-Hee Kang & Soon-Ryul Nam, 2016. "A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids," Energies, MDPI, vol. 9(6), pages 1-16, June.
    2. Changchun Cai & Haolin Liu & Weili Dai & Zhixiang Deng & Jianyong Zhang & Lihua Deng, 2017. "Dynamic Equivalent Modeling of a Grid-Tied Microgrid Based on Characteristic Model and Measurement Data," Energies, MDPI, vol. 10(12), pages 1-16, November.
    3. Hussain, Akhtar & Bui, Van-Hai & Kim, Hak-Man, 2019. "Microgrids as a resilience resource and strategies used by microgrids for enhancing resilience," Applied Energy, Elsevier, vol. 240(C), pages 56-72.
    4. Ying-Yi Hong, 2016. "Electric Power Systems Research," Energies, MDPI, vol. 9(10), pages 1-4, October.
    5. Yang Xiao & Libing Zhou & Jin Wang & Rui Yang, 2017. "Finite Element Computation of Transient Parameters of a Salient-Pole Synchronous Machine," Energies, MDPI, vol. 10(7), pages 1-18, July.

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