Allocation of the load profiles to consumers using probabilistic neural networks

被引:117
作者
Gerbec, D [1 ]
Gasperic, S
Smon, I
Gubina, F
机构
[1] Univ Ljubljana, Fac Elect Engn, Lab Power Syst, SI-1000 Ljubljana, Slovenia
[2] Elektro Gorenjska Distribut Co, SI-4000 Kranj, Slovenia
关键词
cluster analysis; fuzzy logic; load profiles; power distribution; probabilistic neural networks; wavelet analysis;
D O I
10.1109/TPWRS.2005.846236
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The new emerged operating conditions in the power sector are forcing the power-market participants to develop new tools. Among them, load profiles are a key issue in retail power markets. For various types of small consumers without quarter-hourly load measurements, determination of typical load profiles (TLPs) could serve as a tool for determining of their load diagrams. Their main function is in billing of consumers who have deviated from their contracted schedules. Moreover, a simple and straightforward method for assigning a TLP to a particular eligible consumer also needs to be established. In this paper, a methodology for allocating consumers' load profiles using probabilistic neural network (PNN) is presented. It is based on the preprocessed measured load profiles (MLPs), using wavelet multiresolution analysis, clustered with a FCM clustering algorithm with an appropriate cluster-validity measure. The results demonstrate the efficiency of the formation procedure for the proposed TLPs.
引用
收藏
页码:548 / 555
页数:8
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