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In order to reduce load fluctuations and network losses caused by large-scale electric vehicles connected to the distribution network, this paper proposed a multi-objective optimization control method based on Particle Swarm Optimization (PSO) algorithm for flexible loads of large-scale electric vehicle charging connected to the distribution network. Firstly, a coupling model between transportation network and distribution network was established, and combine it with the travel chain model to analyze users’ charging needs, and a prediction model for the energy state of connected electric vehicles was established; Secondly, the minimized standard deviation of load fluctuations and network losses in the distribution network was taken as the optimization objective, and a multi-objective optimization function was established for the flexible load integration of large-scale charging of electric vehicles into the distribution network, meanwhile distribution entropy was introduced to design inertia weight update strategy and optimize PSO algorithm. Finally, the improved PSO algorithm was used to achieve flexible load control of the distribution network based on functional constraints. The test results show that the proposed method can accurately analyze the charging needs of users, and reduce the peak load fluctuation and network loss of the controlled distribution network.
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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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