{"id":9796,"date":"2026-08-09T14:38:31","date_gmt":"2026-08-09T06:38:31","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=9796"},"modified":"2026-08-09T16:02:34","modified_gmt":"2026-08-09T08:02:34","slug":"jase-202611-34-029","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=jase-202611-34-029","title":{"rendered":"Analysis of the microgrid’s frequency resilience using a lightweight selfish sheep optimisation algorithm"},"content":{"rendered":"\n
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<\/i> 2026<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 34<\/a><\/p>\n<\/div>\n\n\n\n

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Anjiang Liu<\/i><\/a>, Youzhuo Zheng, Di Weng, Hengrong Zhang, and Xinhao Li<\/p>\n\n\n\n

Electric Power Research Institute, Guizhou Power Grid Co., Ltd, Guiyang, 550002, China<\/p>\n<\/div>\n\n\n\n

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Received: March 19, 2026
Accepted: April 23, 2026
Publication Date: August 09, 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

\"\u4e0a\u50b3\u5716\u7247\"\n\n\n

MG model for analysis of frequency stability<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:\u00a0 BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.202611_34.029<\/a>\u00a0\u00a0<\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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The lightweighting problem in microgrid (MG) simulation models is first officially described in this paper as an optimisation assignment with the goal of minimising the disturbances to the microgrid frequency robustness. This paper formally presents the lightweighting problem in microgrid (MG) simulations as an optimization task aimed at minimizing frequency disturbances. We propose a Selfish Herd Optimization (SHO)-based technique and its FA-SHO enhancement, using group and predator parameters to model prey\u2013predator interactions. The algorithms optimize gain values and controllers to improve system robustness. Experimental results show that FA-SHO outperforms SHO, with faster convergence, lower error metrics, and better frequency response, while the SMC ensures strong dynamic stability and resilience.<\/p>\n\n\n\n

Keywords: microgrid, lightweight algorithm, selfish flock optimization, voltage stability control, SHO algorithm, FA-SHO algorithm<\/em><\/p>\n\n\n\n

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