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Bacterial Foraging Algorithm based Parameter Estimation of Three WINDING Transformer

机译:基于细菌觅食算法的三绕组变压器参数估计

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Transformers are one of the main components of any power system. An accurate estimation of system be-haviour, including load flow studies, protection, and safe control of the system calls for an accurate equiva-lent circuit parameters of all system components such as generators, transformers, etc. This paper presents a methodology to estimate the equivalent circuit parameters of the Three Winding Transformer (TWT) using Bacterial Foraging Algorithm (BFA). The estimation procedure based on load test data at one particular op-erating point namely supply voltage, load currents, input power. The performance characteristics, such as efficiency and voltage regulation are considered along with the name plate data in order to minimize the er-ror between the estimated and measured data. The estimation procedure is demonstrated with a sample three winding transformer and the results are compared against the directly measured performance of TWT and genetic algorithm optimization results. The simulation results show the ability of the proposed technique to capture the true values of the machine parameters and the superiority of the results obtained using the bacte-rial foraging algorithm.
机译:变压器是任何电力系统的主要组件之一。准确估计系统性能,包括潮流研究,保护和系统安全控制,要求所有系统组件(例如发电机,变压器等)的精确等效电路参数。本文提出了一种估计方法使用细菌觅食算法(BFA)的三绕组变压器(TWT)的等效电路参数。基于某一特定工作点上的负载测试数据(即电源电压,负载电流,输入功率)的估算程序。为了使估计数据和测量数据之间的误差最小,将性能特性(例如效率和电压调节)与铭牌数据一起考虑在内。用一个样本三绕组变压器演示了估计程序,并将结果与​​直接测量的TWT性能和遗传算法优化结果进行了比较。仿真结果表明,所提出的技术具有捕获机器参数真实值的能力,并且具有使用细菌随机觅食算法获得的结果的优越性。

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