Virtual synchronous generator control strategy based on improved cuckoo search algorithm

Disheng Liu; Jianmei Xiao

doi:10.1117/12.3030132

5 June 2024 Virtual synchronous generator control strategy based on improved cuckoo search algorithm

Disheng Liu, Jianmei Xiao

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 1316379 (2024) https://doi.org/10.1117/12.3030132
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

With the development of the times, new energy power generation and grid-connected technology is increasingly developed, and virtual synchronous generator (VSG) control technology is widely used to improve the grid stability of the power system of new energy power generation. The traditional VSG control system has more parameters with complex design, and the virtual inertia and damping parameters in the VSG determined artificially cannot be optimized, which has some influence on improving the stability of the power system. Since the traditional cuckoo search (CS) algorithm cannot optimize the virtual inertia and damping parameters of VSG. Therefore, to address this problem, this paper introduces chaotic mapping and adaptive change of search step to improve the algorithm's optimization ability and convergence speed on the basis of the original CS algorithm. The improved CS algorithm is used to optimize the parameters of the VSG, and the comparison of the simulation results under frequency fluctuation shows that the algorithm can effectively enhance the stability of the system.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Disheng Liu and Jianmei Xiao "Virtual synchronous generator control strategy based on improved cuckoo search algorithm", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 1316379 (5 June 2024); https://doi.org/10.1117/12.3030132

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