Determination of Typical Load Profile of Consumers using Fuzzy C-Means Clustering Algorithm
Md. Jahangir Hossain1, A. N. M. Enamul Kabir2, Md Mostafizur Rahman3, Borhan Kabir4, Md Rafiqul Islam5
1Md. Jahangir Hossain, Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, (KUET), Khulna, Bangladesh.
2A.N.M. Enamul Kabir, Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
3Md Mostafizur Rahman, Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
4Borhan Kabir, Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
5Md. Rafiqul Islam Department of Electrical & Electronic Engineering, Khulna University of Engineering & Technology, Khulna, Bangladesh.
Manuscript received on October 04, 2011. | Revised Manuscript received on October 21, 2011. | Manuscript published on November 05, 2011. | PP: 169-173 | Volume-1 Issue-5, November 2011. | Retrieval Number: E0181091511/2011©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper reports the Typical Load Profile of different types of consumers of distribution feeder which is based on clustering methods. Among many clustering methods, fuzzy c-means has been examined for determination of representative clusters because fuzzy logic is conceptually easy to understand. It is a well known clustering algorithm for typical load profiles determination. The results demonstrate that the proposed method is efficient for assigning Typical Load Profile (TLP) to the consumers. Moreover, the finding shows that the energy consumption can be clustered not only based on the load pattern but also load value. The results demonstrate that the proposed method is efficient for assigning TLP to the consumers.
Keywords: Deregulation, Load Profile, Fuzzy Clustering Algorithm, Optimum Cluster, Probability, Neural network.