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A novel hybrid optimization approach for reactive power dispatch problem considering voltage stability index

机译:考虑电压稳定性指标的无功功率分发问题的新型混合优化方法

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This paper proposes a novel, reliable, and effective hybrid approach based on the integration of the firefly algorithm (FA) and the adaptive particularly tunable fuzzy particle swarm optimization (APT-FPSO) method to address reactive power dispatch (RPD) problem, a crucial optimization problem in the operation of power systems. Similar to many other original meta-heuristic optimization techniques, the standard FA suffers from some severe drawbacks, most importantly being easily trapped into a locally optimal solution. In order to tackle these difficulties, in the current study, an improved version of fuzzy-based particle swarm optimization is utilized in the internal structure of the original FA. The developed hybrid approach, which is capable of avoiding premature convergence of the original FA by enhancing exploration and exploitation procedures, is employed to determine the optimum control variables (i.e., the voltage of generation buses, tap positions of tap-changer transformers, and reactive power output of shunt compensators) through optimizing three distinct objective functions consisting of total transmission real power loss, the voltage magnitude deviations as well as voltage stability index. To validate the accuracy and competency of the proposed hybrid approach, it is firstly used for solving several benchmark optimization functions and then applied to three test systems at different scales, consisting of IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus power systems, for solving the RPD problem. Eventually, the results of the presented hybrid method will be compared to those obtained by other implemented swarm intelligence-based approaches. The statistical analysis of this research substantiates the robustness and effectiveness of the developed algorithm to handle sophisticated optimization problems, particularly the RPD problem.
机译:本文提出了一种基于萤火虫算法(FA)和自适应特别可调的模糊粒子群优化(APT-FPSO)方法来解决无功功率调度(RPD)问题的新颖,可靠和有效的混合方法。至关重要的电力系统运行中的优化问题。与许多其他原始的元启发式优化技术类似,标准FA遭受了一些严重的缺点,最重要的是容易被困在局部最佳的解决方案中。为了解决这些困难,在本研究中,在原始FA的内部结构中使用了一种改进的模糊粒子群优化版本。通过增强勘探和开发程序,采用开发的混合方法,其能够通过增强勘探和开发程序来避免原始FA过早收敛,以确定最佳控制变量(即,发电总线的电压,抽头更换器变压器的敲击位置和反应性顺式补偿器的电源输出)通过优化三个不同的目标功能,包括总传输实际功率损耗,电压幅度偏差以及电压稳定性指标。为了验证所提出的混合方法的准确性和能力,首先用于解决几个基准优化功能,然后应用于不同尺度的三个测试系统,包括IEEE 30-BUS,IEEE 57总线和IEEE 118总线。电力系统,用于解决RPD问题。最终,将呈现的混合方法的结果与其他实施的群体基于智能的方法获得的结果进行比较。本研究的统计分析证实了发达算法处理复杂优化问题,特别是RPD问题的鲁棒性和有效性。

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