Impact of Dependence on State Identification Results in Distribution Grids Using Copula Theory
Research output: Contribution to book/conference proceedings/anthology/report › Conference contribution › Contributed › peer-review
Contributors
Abstract
Distribution system state identification belongs to one of the most fundamental parts of modern smart grid operation strategies. The quality of identified system states is essential for subsequent algorithms. This paper deals with the impact of dependence on state identification results. Therefore, dependent data samples are generated using Copula theory with different dependence characteristics. The results of multiple Monte Carlo simulations reveal a strong influence of both degree of dependence and dependence structure on state identification errors.
Details
| Original language | German |
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| Title of host publication | NEIS 2017; Conference on Sustainable Energy Supply and Energy Storage Systems |
| Publisher | VDE Verlag, Berlin [u. a.] |
| Pages | 1-7 |
| Number of pages | 7 |
| ISBN (print) | 978-3-8007-4445-9 |
| Publication status | Published - 22 Sept 2017 |
| Peer-reviewed | Yes |
Conference
| Title | NEIS 2017; Conference on Sustainable Energy Supply and Energy Storage Systems |
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| Duration | 21 - 22 September 2017 |
| Location | Hamburg, Germany |
External IDs
| ORCID | /0000-0001-8439-7786/work/142244131 |
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