Power Load Characteristic Classification Technology Research Based onan Optimal Fuzzy C-means Clustering Algorithm
[1]ZHAO Guosheng,NIU ZhenzhenLIU Yongguang,SUN Chaoliang.Power Load Characteristic Classification Technology Research Based onan Optimal Fuzzy C-means Clustering Algorithm[J].Journal of Zhengzhou University (Engineering Science),2015,36(06):52-.[doi:10.3969/j. issn.1671 -6833.2015.06.010]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
36
Number of periods:
2015 06
Page number:
52-
Column:
Public date:
2015-12-25
- Title:
- Power Load Characteristic Classification Technology Research Based onan Optimal Fuzzy C-means Clustering Algorithm
- Keywords:
- load clustering; FCM; load characteristic; daily load curve
- CLC:
- TN929.1
- DOI:
- 10.3969/j. issn.1671 -6833.2015.06.010
- Abstract:
- In view of the disadvantages of the traditional Fuzny C-means clustering algorithm,the author pro-poses an adaptive FCM algorithm.This algorithm is based on two clustering results evaluation index of withinthe class distance MIA and between the class distance MDC.The ratio of MDC and MIA,defined as l,is anadaptive function to determine the clustering number c of FCM algorithm. At the same time,according to thefuzzy decision method,we use the objective function and partition entropy of FCM algorithm together to deter-mine the value of optimal fuzzy weighted m.This algorithm not only overcomes the FCM algorithm disadvan-tage of not being able to determine the clustering number automatically and fuzzy weighted index needs to begiven by experience,but also the clustering result is optimal.Finally,the correctness and effectiveness of thealgorithm were proved through example analysis.
- References:
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