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K. S. Huang, W. Kent, Q. H. Wu and D. R. Turner, “Parameter Identification of an Induction Machine Using Genetic Algorithms,” Proceedings of the Computer Aided Control System Design, USA, 22-27 August, 1999, pp. 510-515. doi: 10.1109/CACSD.1999.808700

has been cited by the following article:

  • TITLE: Bacterial Foraging Algorithm based Parameter Estimation of Three WINDING Transformer

    AUTHORS: Srikrishna Subramanian, Seeni Padma

    KEYWORDS: Parameter Estimation, Three Winding Transformer, Bacterial Foraging Algorithm

    JOURNAL NAME: Energy and Power Engineering, Vol.3 No.2, May 18, 2011

    ABSTRACT: 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.