Full
Outline
With the integration of dispatchable resources such as distributed photovoltaics and energy storage into the distribution network, the demand for dynamic frequency regulation capability in the system has significantly increased, posing comprehensive challenges to load frequency stability control. To better mitigate frequency fluctuations in the new energy distribution network system, a new energy distribution network load frequency control strategy considering source load storage dispatchable resources is proposed. Firstly, based on the frequency response characteristics of distributed photovoltaic, energy storage equipment, and demand side interruptible loads, a load frequency control model for the new energy distribution network was established; Then, based on model predictive control, frequency adjustment was achieved without difference, and the control parameters were adaptively adjusted using deep learning algorithms. A multidimensional index system was constructed to comprehensively evaluate the control performance of the proposed control strategy; Finally, the effectiveness of the proposed method was verified through Matlab/Simulink simulation.
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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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