Estimation of parameters of metal-oxide surge arrester models using Big Bang-Big Crunch and Hybrid Big Bang-Big Crunch algorithms
Metal oxide surge arrester accurate modeling and its parameter identification are very important for insulation coordination studies, arrester allocation and system reliability. Since quality and reliability of lightning performance studies can be improved with the more efficient representation of t...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Shahrood University of Technology
2016-07-01
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| Series: | Journal of Artificial Intelligence and Data Mining |
| Subjects: | |
| Online Access: | http://jad.shahroodut.ac.ir/article_578_564d25a1c25858e62346d530acbaaa91.pdf |