Ahead of Print article ยท Journal article
Reliability Worth Analysis of Distribution Systems Using Cascade Correlation Neural Networks
University of New South Wales1
Department of Electrical Engineering, Technical University of Denmark2
Center for Electric Power and Energy, Centers, Technical University of Denmark3
Smart Electric Components, Center for Electric Power and Energy, Centers, Technical University of Denmark4
Nanyang Technological University5
Shiraz University of Technology6
University of Sharjah7
Reliability worth analysis is of great importance in the area of distribution network planning and operation. The reliability worth's precision can be affected greatly by the customer interruption cost model used. The choice of the cost models can change system and load point reliability indices. In this study, a cascade correlation neural network is adopted to further develop two cost models comprising a probabilistic distribution model and an average or aggregate model.
A contingency-based analytical technique is adopted to conduct the reliability worth analysis. Furthermore, the possible effects of adding distributed generation units into the network are evaluated. The proposed approach has been tested on a radial distribution test network evaluating the reliability worth.
The results show that the probabilistic distribution model provides a more realistic model for the reliability analysis.
Language: | English |
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Publisher: | IEEE |
Year: | 2018 |
Pages: | 412-420 |
ISSN: | 08858950 and 15580679 |
Types: | Ahead of Print article and Journal article |
DOI: | 10.1109/TPWRS.2017.2705185 |
ORCIDs: | Agelidis, Vassilios |