Full
Outline
Against the backdrop of global energy structure transformation and rapid development of renewable energy, how to achieve efficient aggregation and optimized scheduling of heterogeneous virtual power plants (VPPs) has become an important challenge. A heterogeneous VPPs frequency and power coordination scheduling model based on target cascade analysis method is proposed by improving the deep integration of clustering algorithm and control system. Introducing a learning mechanism to optimize the clustering process of photovoltaic battery energy storage systems (PVpBESSs) to meet the energy capacity requirements of a large number of power sources. A distributed control system for PVpBESSs was designed and validated on IEEE 13 node distributed photovoltaic power and energy storage systems. The experimental results show that compared with traditional scheduling methods, the scheduling efficiency has been improved by 18%. The model stabilizes the voltage deviation within 1% and maintains the frequency deviation at around 50 Hz; At the same time, the distribution of battery charging status is evenly maintained at 30%~90%, and efficient collaborative scheduling of photovoltaic and energy storage resources is achieved. Compared to methods that do not use learning mechanisms, the proposed model has strong practicality and potential for expansion, providing a new path for the practical application of virtual power plants.
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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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