Аdaptive Сontrol algorithm Based on a Virtual Synchronous Generator. Part II

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Resumo

An increase in the penetration level of power plants based on renewable energy sources using power converters (PCs) has a direct impact on the dynamic characteristics of modern electric power system (EPS) and, as a consequence, the nature of the transient processes. One of the main problems in such EPS is a significant change in the magnitude of the total inertia of the system over time, which leads to an increase in the rate of change of frequency and the magnitude of its maximum deviation under various disturbances. A promising direction for solving this problem is the synthesis of new structures of PC control systems based on a virtual synchronous generator (VSG) with adaptively changing parameters. The results of the research in this area are presented in the paper, which consists of two parts. In the first part of the paper, the dependence of the adaptive algorithms efficiency for controlling the parameters of the VSG on the structure used is substantiated. A comparative analysis of the developed modified VSG structure with traditional algorithms is performed and its fundamental advantages are proved. The second part of the article presents an analysis of the influence of the modified structure parameters of the VSG on the dynamic response using time domain transient analysis. Based on the results obtained, adaptive algorithms for independent control of virtual inertia and parameters of the VSG damper winding have been developed. The performed mathematical modeling confirmed the reliable and efficient operation of the developed adaptive control algorithms and the modified structure of the VSG as a whole. From the theoretical and experimental results obtained in the paper, it follows that there is a need for simultaneous development and improvement of adaptive control algorithms and the VSG structures used for this.

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Sobre autores

A. Suvorov

Tomsk Polytechnic University

Email: aba7@tpu.ru
Rússia, Tomsk

A. Askarov

Tomsk Polytechnic University

Autor responsável pela correspondência
Email: aba7@tpu.ru
Rússia, Tomsk

N. Ruban

Tomsk Polytechnic University

Email: aba7@tpu.ru
Rússia, Tomsk

Yu. Bay

Tomsk Polytechnic University

Email: aba7@tpu.ru
Rússia, Tomsk

Bibliografia

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  2. Li J., Wen B., Wang H. Adaptive Virtual Inertia Control Strategy of VSG for Micro-Grid Based on Improved Bang-Bang Control Strategy // IEEE Access, 2019. V. 7. P. 39509–39514. https://doi.org/ 10.1109/ACCESS.2019.2904943
  3. Malekpour M., Kiyoumarsi A., Gholipour M. A hybrid adaptive virtual inertia controller for virtual synchronous generators // International Transactions on Electrical Energy Systems, 2021. V. 31(7). e12913. https://doi.org/ 10.1002/2050-7038.12913
  4. Fang H., Yu Z. Improved virtual synchronous generator control for frequency regulation with a coordinated self-adaptive method // CSEE Journal of Power and Energy Systems, 2020. https://doi.org/ 10.17775/CSEEJPES.2020.01950. (в печати)
  5. Zheng T. et al. Adaptive Damping Control Strategy of Virtual Synchronous Generator for Frequency Oscillation Suppression // 12th IET International Conference on AC and DC Power Transmission, 2016. P. 1–5. https://doi.org/ 10.1049/cp.2016.0458
  6. Shi K. et al. Rotor inertia adaptive control and inertia matching strategy based on parallel virtual synchronous generators system // IET Generation, Transmission & Distribution, 2020. V. 14(10). P. 1854–1861. https://doi.org/ 10.1049/iet-gtd.2019.1394
  7. Wang Q. et al. Improved Adaptive Inertia and Damping Coefficient Control Strategy of VSG Based on Optimal Damping Ratio // International Power Electronics Conference (IPEC-Himeji 2022-ECCE Asia), 2022. P. 102–107. https://doi.org/ 10.23919/IPEC-Himeji2022-ECCE53331.2022.9806825
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  13. Li D. et al. A Self-Adaptive Inertia and Damping Combination Control of VSG to Support Frequency Stability // IEEE Transactions on Energy Conversion, 2017. V. 32(1). P. 397–398. https://doi.org/ 10.1109/TEC.2016.2623982e,hfnm
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2. Fig. 1. Transient response of angular frequency deviation at different values of constant inertia.

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3. Fig. 2. The Vyshnegradsky diagram in coordinates A, B with lines of equal largest values of the module furthest from the imaginary axis of the root (p) and equal speed (n).

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4. Fig. 3. (a) points No. 1 and No. 2 on the plane in the axes A, B, differing in the value of p; (b) the transient characteristics of the angular frequency deviation corresponding to the coordinates of points No. 1 and No. 2 and considered at the acceleration stage.

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5. Fig. 4. (a) points No. 1 and No. 2 on the plane in the axes A, B, differing in the value of n; (b) the transient characteristics of the angular frequency deviation corresponding to the coordinates of points No. 1 and No. 2 and considered at the braking stage.

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6. Fig. 5. Graph of the change in the coefficient kH1.

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7. Fig. 6. Graph of changes in the virtual inertia of the VSG.

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8. Fig. 7. Graph of the change in the coefficient kH2.

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9. Fig. 8. The effect of changes in the inertia of the VSG on the rate of frequency change in different embodiments of the sigmoidal function.

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10. Fig. 9. The nature of the change in the coefficient kH4.

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11. Fig. 10. The principle of operation of the algorithm of adaptive inertia VSG.

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12. Fig. 11. The nature of the change in virtual inertia when the frequency changes.

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13. Fig. 12. Oscillograms of current changes in the damper winding during disturbances.

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14. Fig. 13. The principle of operation of the algorithm of adaptive virtual damper winding VSG.

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15. Fig. 14. Simulation results for different disturbances: (a) Rust change; (b) network frequency change; (c) load surge.

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16. Fig. 15. Histograms with characteristics of transients under different disturbances: (a) Rust change; (b) network frequency change; (c) load surge.

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17. Fig. 16. Oscillograms of processes with load loading and different df/dtf setpoints: (a) frequency VSG; (b) the rate of change of frequency and the setpoint value df/dtf; (c) inertia with different algorithms.

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