Jipeng Gu1, Weijie Zhang1, Youbing Zhang1,*, Binjie Wang1, Wei Lou2, Mingkang Ye3, Linhai Wang3, Tao Liu4
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2221-2236, 2023, DOI:10.32604/cmes.2023.025396
Abstract An improved fuzzy time series algorithm based on clustering is designed in this paper. The algorithm is successfully applied to short-term load forecasting in the distribution stations. Firstly, the K-means clustering method is used to cluster the data, and the midpoint of two adjacent clustering centers is taken as the dividing point of domain division. On this basis, the data is fuzzed to form a fuzzy time series. Secondly, a high-order fuzzy relation with multiple antecedents is established according to the main measurement indexes of power load, which is used to predict the short-term trend change of load in the… More >
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