This article proposes a new differential evolutionary-based approach to solve the optimal power flow (OPF) problem in power systems. The proposed approach employs a differential-based harmony search algorithm (DH/best) for optimal settings of OPF control variables. The proposed algorithm benefits from having a more effective initialization method and a better updating procedure in contrast with other algorithms. Here, real power losses minimization, voltage profile improvement, and active power generation minimization are considered as the objectives and formulated in the form of single-objective and multi-objective functions. For proving the performance of the proposed algorithm, comprehensive simulations have been performed by MATLAB software in which IEEE 118-bus and 57-bus systems are considered as the test systems. Besides, thorough comparisons have been performed between the proposed algorithm and other well-known algorithms like PSO, NSGAII, and Harmony search in three different load levels indicating the higher efficiency and robustness of the proposed algorithm in contrast with others.

本文提出了一种新的基于差分进化的方法来解决电力系统中的最佳潮流（OPF）问题。所提出的方法采用基于差分的和声搜索算法（DH /最佳）来优化OPF控制变量的设置。与其他算法相比，所提出的算法受益于更有效的初始化方法和更好的更新过程。这里，将实际功率损耗最小化，电压分布改善和有功功率生成最小化视为目标，并以单目标和多目标函数的形式制定。为了证明所提出算法的性能，已通过MATLAB软件进行了全面的仿真，其中以IEEE 118总线和57总线系统为测试系统。除了，