首页> 外文OA文献 >Improved multi-objective artificial bee colony algorithm for optimal power flow problem
【2h】

Improved multi-objective artificial bee colony algorithm for optimal power flow problem

机译:改进的多目标人工蜂群算法求解最优潮流问题

摘要

The artificial bee colony (ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow (OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
机译:改进了人工蜂群(ABC)算法,构造了一种混合多目标ABC算法,称为HMOABC,该算法通过同时优化OPF的三个冲突目标来解决最优潮流(OPF)问题,而不是将多目标函数转换为最优目标。单一目标函数。 HMOABC的主要思想是通过结合Pareto优势和分而治之的方法将原始ABC算法扩展到多目标合作模式。然后,将HMOABC用于30总线IEEE测试系统中,以考虑到成本,损失和排放影响来解决OPF问题。仿真结果表明,HMOABC在优化精度和计算鲁棒性方面优于其他算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号