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首页> 外文期刊>Journal of control, automation and electrical systems >Merging Lion with Crow Search Algorithm for Optimal Location and Sizing of UPQC in Distribution Network
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Merging Lion with Crow Search Algorithm for Optimal Location and Sizing of UPQC in Distribution Network

机译:用乌鸦搜索算法合并狮子,以实现分销网络的最佳位置和UPQC尺寸

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Unified power quality conditioner (UPQC) is exploited to alleviate the issues associated with voltage swell/dip in source voltage, and it regulates the load voltage absolutely. It is deployed to resolve the entire issues associated with current and voltage harmonics and enhance power quality. In order to solve those issues, optimal sizing and location of UPQC are adopted by the researchers, and it is still in progress. However, the power quality issues like power loss, UPQC cost and voltage stability index (VSI) are not analysed and considered. Hence, the tactics used in this paper help to design an optimal location and sizing of the UPQC in power system using a nonlinear multi-objective function. The objective function considers the minimization of power loss, UPQC cost and VSI. For attaining this objective, this paper hybridizes two well-performed optimization algorithms called lion algorithm (LA) and crow search algorithm (CSA). Since the mating of LA is carried out on the basis of CSA update, the proposed algorithm is termed as crow search mating-based lion algorithm (CSM-LA). The current experiment on localizing and sizing of UPQC is carried out in IEEE 33 and IEEE 69 benchmark test bus systems. The performance of the proposed model is distinguished with conventional methods in terms of performance and convergence analysis, and the relevant outcomes are attained which proves the superiority of the proposed model.
机译:利用统一的电能质量调节器(UPQC)以缓解与电源电压的电压膨胀/倾达相关的问题,并且它绝对调节负载电压。部署它以解决与电流和电压谐波相关的整个问题,提高电能质量。为了解决这些问题,研究人员采用了最佳规模和UPQC的位置,并且仍在进行。但是,不分析和考虑电力损耗,UPQC成本和电压稳定性指数(VSI)等电力质量问题。因此,本文中使用的策略有助于使用非线性多目标函数设计在电力系统中的最佳位置和大小。目标函数考虑最小化功率损耗,UPQC成本和VSI。为了实现这一目标,本文涉及两个称为狮子算法(LA)和乌鸦搜索算法(CSA)的良好进行的优化算法。由于LA的配合是在CSA更新的基础上进行的,所以所提出的算法被称为乌鸦搜索配合的狮子算法(CSM-LA)。目前在IEEE 33和IEEE 69基准测试总线系统中执行了UPQC的定位和尺寸的实验。在性能和收敛分析方面,拟议模型的性能与传统方法不同,达到了相关结果,证明了所提出的模型的优越性。

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