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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Liu Yingying Li Guodong Gu Qiang Xu Yonghai |
| Copyright Year | 2006 |
| Description | Author affiliation: Key Lab. of Power Syst. Protection & Dynamic Security Monitoring & Control, North China Electr. Power Univ., Beijing (Liu Yingying; Li Guodong; Gu Qiang; Xu Yonghai) |
| Abstract | The power quality comprehensive evaluation (PQCE) is the foundation of deciding the price according to the quality of power commodity as well as a part of the ancillary service in power market. A new method based on the radial basis function (RBF) neural network for PQCE is proposed in the paper. According to the national standards of P.R. China, this paper made the grades of each power quality index. Efficient samples based on the random-distribution theory were produced to train the network The RBF neural network with high non-linearity-fitting capacity was applied to the PQCE, which overcame the shortages such as uncertainty and man-influenced in fuzzy mathematics, probability and mathematical statistics and analytic hierarchy process (AHP). The RBF neural network-based model possessed the objective and rationalization. The practical example for PQCE on the substations approved that the proposed approach is reasonable and feasible. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 5235005 |
| Page Count | 5 |
| File Format | |
| ISBN | 1424401100 |
| DOI | 10.1109/ICPST.2006.321429 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2006-10-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Radial basis function networks Power quality Neural networks Power markets Capacity planning Uncertainty Fuzzy neural networks Mathematics Probability Statistical analysis Comprehensive evaluation Power system Transmission and distribution RBF neural network |
| Content Type | Text |
| Resource Type | Article |
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