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In response to the issue that the randomness and volatility of wind power can affect the vulnerability assessment of the power grid and the identification of critical nodes, this paper proposes an intervalbased Electrical DebtRank algorithm to identify vulnerable nodes within the power grid. The method first incorporates the node's offset status and characteristics to improve the traditional Electrical DebtRank algorithm. Then, interval numbers are used to represent the randomness and volatility of wind power generation, leading to the development of the interval – based Electrical DebtRank algorithm to identify vulnerable nodes in a windintegrated power system. Finally, simulation results on the IEEE118 bus system demonstrate that when the vulnerable nodes identified by the proposed method are attacked, the system's power supply capability drops to 33% of its normal state, with a significant reduction in the system's power transmission capacity.
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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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