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- W2981837327 abstract "This paper proposes an efficient abnormal load identification method in large-scale power system employing Rayleigh quotient method and parallel computing techniques. It firstly constructs a group of data source matrices with random load fluctuation and noise interference for each zone, respectively. Then their standard matrices and the sample covariance matrices of each zone can be formed. Secondly, the maximum eigenvalue of sample covariance matrix (MESCM) for each zone could be acquired rapidly with the help of the Rayleigh quotient method and the parallel computing techniques. In this way, the rapid identification of abnormal load may be achieved by the violation checking of MESCM. Utilizing PST and Matlab® software, the case studies have been carried on an IEEE 54-machine and 118-bus system and a Polish 420-machine and 2736-bus system. The results in comparison with the traditional mean spectral radius(MSR) based method show that the proposed methodology is valid and efficient." @default.
- W2981837327 created "2019-11-01" @default.
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- W2981837327 date "2019-05-01" @default.
- W2981837327 modified "2023-09-25" @default.
- W2981837327 title "Efficient Abnormal Load Identification in Large-Scale Power System employing Rayleigh Quotient Method and Parallel Computing Techniques" @default.
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- W2981837327 doi "https://doi.org/10.1109/isgt-asia.2019.8881717" @default.
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