TITLE:
Study on Identification of Inductive-Motors Load Partition Based on Coherence
AUTHORS:
Chengjun Xia, Yun Zhou, Kun Men, Yinggeng Xie
KEYWORDS:
Study on Identification of Inductive-Motors Load Partition Based on Coherence
JOURNAL NAME:
Journal of Power and Energy Engineering,
Vol.2 No.9,
September
17,
2014
ABSTRACT: A new inductive motors load
equivalence algorithm based on coherence is proposed in this paper. In order to
partite motors load rapidly and accurately, fuzzy c-means clustering along with
particle swarm optimization (PSO-FCM) algorithm is proposed to identify
coherent motors base on its physical essence of fuzziness. The merits of PSO
algorithm are independent to initial value and convergent to optimum value
rapidly, and the validity function is constructed to assess clustering
validity. The test on IEEE 39-Bus System is presented to evaluate the
effectiveness of the new algorithm, the membership matrix definite not only
coherence group of motors but also correlation value of coherence between
motors. The algorithm can be used to partite motor load based on coherency in
dynamic equivalence with power system operating on different modes.