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Optimal Power Flow Using Artificial Bee Colony, Wind Driven Optimization and Gravitational Search Algorithms

机译:利用人工蜂群,风力驱动优化和引力搜索算法的最佳潮流

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In this study, artificial bee colony, wind driven optimization and gravitational search algorithms are employed in order to solve the optimal power flow problem. The proposed optimization approaches are tested on the standard IEEE 9-bus power system with the objective functions of voltage deviation reduction, active power loss minimization and fuel cost minimization. In addition, the calculation time spent is compared. The simulation results show that, on the one hand, the proposed optimization approaches have the similar potentials in the minimization of active power losses and fuel costs. On the other hand, wind driven optimization algorithm ensures more consistent results than the other ones in the reduction of voltage deviation and in terms of the calculation time spent.
机译:在这项研究中,采用人工蜂群,风力驱动优化和重力搜索算法来解决最优潮流问题。所提出的优化方法在标准IEEE 9总线电源系统上进行了测试,其目标功能是降低电压偏差,最小化有功功率损耗和最小化燃料成本。另外,将比较所花费的计算时间。仿真结果表明,一方面,所提出的优化方法在最小化有功功率损耗和燃料成本方面具有相似的潜力。另一方面,在降低电压偏差和减少计算时间方面,风力驱动的优化算法可确保获得比其他算法更一致的结果。

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