计算机与现代化 ›› 2025, Vol. 0 ›› Issue (06): 34-41.doi: 10.3969/j.issn.1006-2475.2025.06.006

• 算法设计与分析 • 上一篇    下一篇

基于改进哈里斯鹰算法的微电网优化调度

  

  1. (吉林建筑大学电气与计算机学院,吉林 长春 130000)
  • 出版日期:2025-06-30 发布日期:2025-07-01
  • 作者简介: 作者简介:段宏瑾(1999—),男,辽宁铁岭人,硕士研究生,研究方向:电网优化调度,E-mail: 18604576983@163.com; 通信作者:张毅(1972—),女,吉林长春人,教授,博士,研究方向:智能电网优化,E-mail: zhangyi@jlju.edu.cn。
  • 基金资助:
     基金项目:吉林省自然基础研究计划资助项目(YDZJ202201ZYTS553)

Optimized Scheduling of Microgrid Based on Improved Harris Eagle Algorithm

  1. (College of Electrical and Computer Science, Jilin Jianzhu University, Changchun 130000, China)
  • Online:2025-06-30 Published:2025-07-01

摘要: 摘要:为了降低微电网运行成本,同时针对传统哈里斯鹰算法容易陷入局部最优的问题,提出一种基于折射成像反向学习策略和混合蝴蝶算法的新型哈里斯鹰算法,将所改进的算法通过11个测试函数进行仿真,所得结果表明改进的哈里斯鹰算法比灰狼算法、鲸鱼算法等传统元启发算法具有更好的寻优精度。将改进的哈里斯鹰算法用于求解微电网孤岛优化调度问题,仿真结果显示,改进的哈里斯鹰算法能够降低微电网的运行成本。


关键词: 关键词:微电网, 哈里斯鹰算法, 蝴蝶算法, 折射成像反向学习, 优化调度

Abstract: Abstract: In order to reduce the operating cost of microgrid and solve the problem that the traditional Harris Eagle algorithm is easy to fall into local optimum, a new Harris Eagle algorithm based on refractive imaging inverse learning strategy and hybrid butterfly algorithm was proposed, and the improved algorithm was simulated through 11 test functions. Then, the improved Harris Eagle algorithm is used to solve the problem of island optimal scheduling of microgrids, and the simulation results show that the improved Harris Eagle algorithm can reduce the operating cost of microgrids.

Key words: Key words: microgrid, Harris hawks optimization, butterfly algorithm, reverse learning of refraction imaging, optimized scheduling

中图分类号: