Full
Outline
To mitigate the fluctuations in the output from micro-sources within a half-bridge converter series Y-connection microgrid (HCSY-MG) grid-connected system and ensure both the balance of the sum of DC-side voltages in each phase and the balance of three-phase grid-connected current, a distributed hybrid energy storage system (HESS) charge-discharge optimal control strategy based on improved proximal policy optimization (PPO) is put forward. With the consideration of grid-connected current in the HCSY-MG system and the characteristics of the distributed HESS, the key system variables affecting the grid-connected current are identified, and the optimal topology for integrating the HESS into the system is determined. Subsequently, by combining the characteristics of the series-connected system, the charge-discharge problem of the distributed HESS is transformed into a Markov decision process within the framework of deep reinforcement learning. Meanwhile, to address the challenge of determining the entropy loss weight in the PPO method, an improved PPO method is proposed, which balances the agent’s convergence and exploration capabilities. Finally, the typical operational data of a renewable energy generation site is used as a case study, and the feasibility and effectiveness of the proposed control strategy is validated.
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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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