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With the increasing penetration of distributed energy in the power system and its output uncertainty, the distribution system presents greater complexity and uncertainty, which will have an impact on the reliability of the power network. In order to determine the optimal installation location and capacity size of renewable units in the distribution network system, this paper proposes a reliability assessment framework by combining the stochastic fuzzy expected value operator and Markov Monte Carlo method. The model first establishes the multi state probability density functions of wind and PV outputs, and subsequently employs the stochastic fuzzy expected value operator to simulate the uncertainties of power loss and voltage stability in the distribution network. The stochastic nature of all nonsource components in the distribution system is modeled using the Markov Monte Carlo method to generate distribution network component failure events and recovery times from an exponential distribution, considering the topology of the distribution system. Three reliability indices, namely, average system outage number, average system outage duration, and power shortage expectation, are evaluated on the IEEE 33 node standard distribution network, and the experimental results demonstrate the effectiveness of the proposed method.
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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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