Application of the k-means clustering algorithm to predict load shedding of the Southern Electrical Grid of Libya
作者： Ahmed Alkilany , Almahdi Ahmed , Hammad Said , Azuraliza Abu Bakar
DOI: 10.1109/INTECH.2014.6927763
关键词:
摘要: In Libya, from time to time, the National Electricity Grid is directed by Company conduct load shedding mitigate pressure on supply at times of peak demand. This involves hours' power outages in area covered this study, namely, Southern Electrical Libya (SEGL). paper discusses results a pattern extraction process using k-means clustering algorithm predict for scenario. The data consist all loads shed 40 electrical stations southern two-year period 2009 through 2010. An experiment was conducted assess effectiveness grouping (clustering) as means future SEGL. Each cluster generated five create different sizes (1, 2, 5, 7 and 10) with seed values. extracted provided information attributes. obtained showed that clusters are fit be used schedule problem
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