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  • 标题:Coot Algorithm for Optimal Carbon–Energy Combined Flow of Power Grid With Aluminum Plants
  • 本地全文:下载
  • 作者:Liangdong Qin ; Tianfeng Xu ; Sheng Li
  • 期刊名称:Frontiers in Energy Research
  • 电子版ISSN:2296-598X
  • 出版年度:2022
  • 卷号:10
  • DOI:10.3389/fenrg.2022.856314
  • 语种:English
  • 出版社:Frontiers Media S.A.
  • 摘要:To achieve a low-carbon and economical operation for the power grid, this paper proposes a novel optimal carbon–energy combined flow (OCECF) by considering the influence of aluminum plants. It attempts to minimize the carbon emission of power grid, power loss, and the voltage deviation by taking the reactive power control of aluminum plants into account. Since the presented OCECF is a nonlinear and complex optimization problem, a new metaheuristic algorithm called Coot algorithm is employed to acquire a high-quality dispatch solution under various scenarios. The Coot algorithm is inspired by the movement of birds on the water surface, which can implement a wide exploration via the random movement and a deep exploitation via the chain movement with the group leaders. The performance of Coot algorithm for the presented OCECF is carried out on an IEEE 57-bus system with various power plants, in which the group search optimizer is introduced for performance comparison.
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