首页> 外文期刊>Global Journal of Technology and Optimization >Hybrid Differential Evolution and Harmony Search for Optimal Power Flow
【24h】

Hybrid Differential Evolution and Harmony Search for Optimal Power Flow

机译:最优功率流的混合差分进化与和谐搜索

获取原文
       

摘要

In this paper, we presents a novel approach for solving optimal power flow (OPF) problems using a hybrid differential evolution and harmony search (DEHS). The DEHS method is an improved differential evolution method based on the harmony search scheme. Harmony Search has strong and easy to combine with other methods in optimization and the Differential Evolution algorithm has a very great ability to search solutions with a fast speed to converge, contrary to the most meta-heuristic algorithms. The DEHS method has the flexible adjustment of the parameters to get a better optimal solution. Moreover, an effective constraint handling framework in the method is employed for properly handling equality and inequality constraints of the problem. The proposed DEHS has been tested on three systems including IEEE-30 bus system with quadratic fuel cost function, IEEE-30 bus system with valve point effects fuel cost function and IEEE-57 bus system with quadratic fuel cost function. The obtained results from DEHS algorithm have been compared to those from other methods in the literature. The result comparison has indicated that the proposed DEHS method is more effective than many other methods for obtaining the optimal solution for the test systems. Therefore, the proposed DEHS is a very favorable method for solving the optimal power flow problems.
机译:在本文中,我们提出了一种使用混合差分演化与和谐搜索(DEHS)解决最优潮流(OPF)问题的新颖方法。 DEHS方法是基于和声搜索方案的改进的差分进化方法。与大多数优化算法相反,“和谐搜索”具有强大且易于与其他方法结合进行优化的优势,“差分进化”算法具有以极快的收敛速度搜索解决方案的强大能力。 DEHS方法可以灵活调整参数,以获得更好的最佳解决方案。此外,在该方法中采用有效的约束处理框架来适当地处理问题的相等性和不平等性约束。提议的DEHS已在三种系统上进行了测试,包括具有二次燃料成本函数的IEEE-30总线系统,具有阀点效应燃料成本函数的IEEE-30总线系统和具有二次燃料成本函数的IEEE-57总线系统。从DEHS算法获得的结果已与文献中其他方法获得的结果进行了比较。结果比较表明,所提出的DEHS方法比许多其他方法更有效地获得测试系统的最佳解决方案。因此,提出的DEHS是解决最佳潮流问题的非常有利的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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