DocumentCode
3470237
Title
An optimized FCM method for electric load clustering
Author
Li, Cailing ; Wang, Jin ; Li, Xinran
Author_Institution
Coll. of Electr. & Inf. Eng., Univ. of Sci. & Technol., Changsha
fYear
2008
fDate
6-9 April 2008
Firstpage
882
Lastpage
886
Abstract
Load modeling is known as one of the most difficult problems in the power system of the world. It is necessary to further research on the load characteristics analysis and load model can be constructed practically via appropriate clustering method to increase the precision and credibility of the power system analysis, control and simulation. Considering the deficiency of traditional hard C-means (HCM), this paper presents an optimized fuzzy C-means (FCM) method for the static load characteristics clustering of 48 substations in Hunan province power grid. Numbers of substation nodes to install measurement units and the location of substations can be inferred from the clustering results, which provides a significant approach for the research on practical load modeling engineering.
Keywords
fuzzy set theory; load (electric); optimisation; power grids; power systems; substations; Hunan province power grid; electric load clustering; fuzzy set theory; hard C-means method; load modeling; optimization theory; optimized FCM method; optimized fuzzy C-means method; power system analysis; power system control; power system simulation; static load characteristics; substations; Clustering methods; Load modeling; Optimization methods; Power system analysis computing; Power system control; Power system measurements; Power system modeling; Power system simulation; Power systems; Substations; clustering analysis; fuzzy sets; load characteristics; load modeling; optimized FCM method;
fLanguage
English
Publisher
ieee
Conference_Titel
Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
Conference_Location
Nanjuing
Print_ISBN
978-7-900714-13-8
Electronic_ISBN
978-7-900714-13-8
Type
conf
DOI
10.1109/DRPT.2008.4523531
Filename
4523531
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