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As the proportion of renewable energy and variable loads in the distribution system gradually increases, the uncertainty of power flow in the distribution network will affect the optimal network topology. Since distributed generation and demand response are affected by the time factor, the topology obtained by modeling at a single time period is difficult to be optimized at different times of the day. To address this uncertainty, this paper proposes a secondorder cone optimizationbased distribution network reconfiguration model for multitemporal tidal flow analysis for billing and demand response. By considering the "sourcestorageload" structure of the actual distribution system, an optimization problem with the objectives of network operation cost and switching operation cost is established, and the secondorder cone relaxation is used to transform the nonconvex search space into a convex feasible domain for fast solution. Experimental results on an improved IEEE 33 node distribution network show the superiority of the proposed method over traditional methods in terms of accuracy and solution speed.
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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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