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    ARTICLE

    A Fault Risk Warning Method of Integrated Energy Systems Based on RelieF-Softmax Algorithm

    Qidai Lin1, Ying Gong2,*, Yizhi Shi1, Changsen Feng2, Youbing Zhang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752

    Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF… More >

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