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Calculation method of distribution network limit line loss rate based on fuzzy clustering
| Content Provider | Scilit |
|---|---|
| Author | Yuan, X. Y. Tao, Y. L. |
| Copyright Year | 2019 |
| Description | Journal: Iop Conference Series: Earth and Environmental Science In view of the characteristics of 10kV distribution network lines, in order to analyze the line loss rate and determine the loss reduction space, this paper proposes a calculation method of the limit line loss rate (LLLR) based on a series of current LLLR indicators. Firstly, according to the difference between different line characteristics and operation parameters of distribution network, the index which has a high impact on the LLLR is screened out, then the clustering index parameters are extracted, and clustering analysis is carried out by using the fuzzy C-means algorithm. According to the clustering results of feeders, the reference feeders are selected for each type of feeders, and the equivalent resistance method is used to calculate the LLLR under the limit conditions. For intra-class non-reference feeders, the adjustment coefficient method is used to calculate the LLLR, and the LLLR is corrected by checking whether the line loss rate obeys the normal distribution. Taking the distribution network data of a city as an example, the LLLR is calculated, which proves the validity of the method. |
| Related Links | https://iopscience.iop.org/article/10.1088/1755-1315/354/1/012029/pdf |
| ISSN | 17551307 |
| e-ISSN | 17551315 |
| DOI | 10.1088/1755-1315/354/1/012029 |
| Journal | Iop Conference Series: Earth and Environmental Science |
| Issue Number | 1 |
| Volume Number | 354 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2019-10-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Iop Conference Series: Earth and Environmental Science Hardware and Architecture Distribution Network Line Loss Rate |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Physics and Astronomy Environmental Science |
