| Autor: |
Kai Liang, Yu Liu, Huan He, Xiangbo Zhu, Zhen Jiao, Qi Wang, Rui Hao |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Energy Reports, Vol 8, Iss , Pp 413-419 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2352-4847 |
| DOI: |
10.1016/j.egyr.2022.10.293 |
| Popis: |
Modern power system is stepping into the era of big data. It is necessary to widely collect multi-source data and mine the load characteristics of load data from different angles. This paper introduces an efficient comprehensive characteristic analysis method of 10 kV bus load based on integrated clustering technology, which includes clustering the load from vertical and horizontal dimensions respectively to obtain the clustering results under the unified time frame. Firstly, K-means clustering and hierarchical clustering are used to establish the load characteristic model for the whole year’s load data, and the daily load characteristics and hourly load characteristics are obtained. Then, the distribution time area of the maximum load and the normal operation threshold of the load are analyzed. Finally, the feasibility of this method is verified through the 24 * 365 load data, which provides convenience for the subsequent power system optimization. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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