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This paper proposes a DC distribution network fault location method combining current integral variation trend and temporal convolutional network (TCN)-support vector machine (SVM), to distinguish and locate DC distribution network faults, and lay the foundation for DC distribution network protection. Firstly, the integral sequence of fault current is calculated, and the integral sequence is decomposed by variational mode decomposition (VMD) algorithm. The eigenvalues of the decomposed high frequency intrinsic mode function are used as the input eigenvectors of the combination model of TCN and SVM, and the fault lines are located and the fault types are determined. The simulation results show that the scheme can not only locate the fault line quickly and identify different faults accurately, but also has good adaptability and certain anti-interference ability.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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