Browse > Article
http://dx.doi.org/10.5370/JEET.2012.7.3.281

Repeated Clustering to Improve the Discrimination of Typical Daily Load Profile  

Kim, Young-Il (S/W Center, KEPCO (Korea Electric Power Cooperation) Research Institute, KEPCO)
Ko, Jong-Min (S/W Center, KEPCO Research Institute, KEPCO)
Song, Jae-Ju (S/W Center, KEPCO Research Institute, KEPCO)
Choi, Hoon (Dept. of Computer Engineering, Chungnam National University)
Publication Information
Journal of Electrical Engineering and Technology / v.7, no.3, 2012 , pp. 281-287 More about this Journal
Abstract
The customer load profile clustering method is used to make the TDLP (Typical Daily Load Profile) to estimate the quarter hourly load profile of non-AMR (Automatic Meter Reading) customers. This study examines how the repeated clustering method improves the ability to discriminate among the TDLPs of each cluster. The k-means algorithm is a well-known clustering technology in data mining. Repeated clustering groups the cluster into sub-clusters with the k-means algorithm and chooses the sub-cluster that has the maximum average error and repeats clustering until the final cluster count is satisfied.
Keywords
Repeated clustering; K-means; Typical load profile; Discrimination; Cosine similarity;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
연도 인용수 순위
1 J.A. Jardini, "Daily Load Profile for Residential, Commercial and Industrial Low Voltage Consumers", IEEE Transaction on Power Delivery, vol.15, pp.375- 380, 2000.   DOI   ScienceOn
2 N.M. Pindoriya, S.N. Singh, and S.K. Singh, "Forecasting of Short-Term Electric Load Using Application of Wavelets with Feed-Forward Neural Networks", International Journal of Emerging Electric Power Systems, vol.11, no.1, pp.1-24, 2010.
3 SanJeev Kumar Aggarwal, Lalit Mohan Saini, and Ashwani Kumar, "Electricity Price Forecasting in Ontario Electricity Market Using Wavelet Transform in Artificial Neural Network Based Model", International Journal of Control, Automation, and Systems, vol.6, no.5, pp.639-650, October 2008.   과학기술학회마을
4 Young-Il Kim, Jin-Ho Shin, Jae-Ju Song, and Il- Kwan Yang, "Customer Clustering and TDLP (Typical Daily Load Profile) Generation Using the Clustering Algorithm", International Conference of IEEE Transmission and Distribution Asia 2009, vol. 1, pp.1-4, 2009.
5 Jain A. K. and Dubes R.C., 1988. "Algorithms for Clustering Data", Englewood Cliffs, NJ: Prentice-Hall.
6 Van Rijsbergen, C. J., "Information Retrieval, 2nd edition", London: Buttersworth, 1979.
7 Lehmann, E.L., and Joseph P. Romano, "Testing Statistical Hypotheses, 3rd edition", New York: Springer, 2005.
8 H. Demuth and M. Beale, "Neural Network Toolbox for Use With MATLAB", Natick, MA: MathWorks, Jun. 2001.
9 David Gerbec, Samo Gasperic, Ivan Smon, and Ferdinand Gubina, "Allocation of the Load Profiles to Consumers Using Probabilistic Neural Networks", IEEE Transactions on Power Systems, Vol. 20, No. 2, May 2005, pp. 548-555.   DOI   ScienceOn
10 Dong-Jun Won, Il-Yop Chung, Joong-Moon Kim, Seon-Ju Ahn, Seung-Il Moon, Jang-Cheol Seo, and Jong-Woong Choe, "Power Quality Monitoring System with a New Distributed Monitoring Structure", KIEE International Transactions on Power Engineering, vol.4-A. no.4, pp.214-220, 2004.   과학기술학회마을
11 Young-Il Kim, Jong-Min Ko, and Seung-Hwan Choi, "Methods for Generating TLPs (Typical Load Profiles) for Smart Grid-Based Energy Programs", IEEE Symposium Series on Computational Intelligence 2011, vol.1, pp.49-54, 2011.
12 Jeong-Do Park, "Unit Commitment for an Uncertain Daily Load Profile", KIEE International Transaction on Power Engineering, vol.5-A, no.1, pp.16-21, 2005.   과학기술학회마을
13 Jong-Young Park, Soon-Ryul Nam, and Jong-Keun Park, "Real-Time Volt/VAr Control Based on the Difference between the Measured and Forecasted Loads in Distribution Systems", Journal of Electrical Engineering and Technology, vol.2, no.2, pp.152-156, 2007.   과학기술학회마을   DOI   ScienceOn