| Autor: |
Junhui Xin, Xiaohu Yu, Rao Yuze, Kunpeng Zhou, Zeyang Tang, Defu Cai, Kan Cao, Wan Li |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
2018 China International Conference on Electricity Distribution (CICED). |
| DOI: |
10.1109/ciced.2018.8592376 |
| Popis: |
Many power utilities have problems with the quality of data about distribution network topology. This affects the operation and maintenance of smart grid, including outage management and line loss. The operation data, such as voltage data whose similarity has been analyzed to verify distribution network connectivity. The most commonly method used to evaluate similarity is correlation analysis. In this paper, correlation analysis and morphology similarity distance (MSD) have been compared when used in distribution network connectivity verification. The results show that the data should be normalized when MSD is used. Four case studies have been carried out in order to compare the performance of the two methods. Results show that when the voltage loss of 10kV feeder is large, the performance of correlation analysis is better than MSD. When the variety range of the voltage curves is small, the performance of MSD is better than correlation analysis. When the voltage curves have catastrophe points, the performance of MSD is better than correlation analysis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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