Abstract
An advanced fuzzy C-mean (FCM) algorithm was proposed for the efficient regional clustering of multi-nodes interconnected systems. Due to various locational prices and regional coherencies for each node and point, modified similarity measure was considered to gather nodes having similar characteristics. The similarity measure was needed to contain locational prices as well as regional coherency. In order to consider the two properties simultaneously, distance measure of fuzzy C-mean algorithm had to be modified. Regional clustering algorithm for interconnected power systems was designed based on the modified fuzzy C-mean algorithm. The proposed algorithm produces proper classification for the interconnected power system and the results are demonstrated in the example of IEEE 39-bus interconnected electricity system.
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Foundation item: Work supported by the Second Stage of Brain Korea 21 Projects; Work(2010-0020163) supported by Priority Research Centers Program through the National Research Foundation (NRF) funded by the Ministry of Education, Science and Technology of Korea
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Wang, Hm., Kim, JH., Jung, DY. et al. Power interconnected system clustering with advanced fuzzy C-mean algorithm. J. Cent. South Univ. Technol. 18, 190–195 (2011). https://doi.org/10.1007/s11771-011-0679-5
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DOI: https://doi.org/10.1007/s11771-011-0679-5