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- W2593140833 abstract "Different from traditional power load pattern analysis methods which classify power load according to industrial properties, the two-step clustering method based on data mining algorithms is used for analyzing the power load patterns of key accounts. This paper analyses the electricity load patterns by processing power usage data of key accounts based on two-step clustering and constructs load clustering analysis model. The index of mean index adequacy (MIA) and mean distance between curves (MDC) are used to evaluate clustering results and determine the optimal number of clustering. Based on an annual load data set of 150 key accounts which include 8 kinds of industries, the practical calculation examples are analyzed. Through the calculation examples, the correctness and the effectiveness of the proposed model are verified. The results show that the method provides reference for power supply departments in the load management of key accounts." @default.
- W2593140833 created "2017-03-16" @default.
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- W2593140833 date "2016-12-23" @default.
- W2593140833 modified "2023-09-24" @default.
- W2593140833 title "Load pattern analysis of key accounts based on two-step clustering" @default.
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- W2593140833 doi "https://doi.org/10.1145/3028842.3028897" @default.
- W2593140833 hasPublicationYear "2016" @default.
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