There have been some research results in the scheduling strategy of the energy storage system of the photovoltaic charging station. It copes with the uncertainty of electric vehicle charging load by optimizing the active and reactive power of energy storage .
Therefore, an optimal operation method for the entire life cycle of the energy storage system of the photovoltaic-storage charging station based on intelligent reinforcement learning is proposed. Firstly, the energy storage operation efficiency model and the capacity attenuation model are finely modeled.
The model is trained by the actual historical data, and the energy storage charging and discharging strategy is optimized in real time based on the current period status. Finally, the proposed method and model are tested, and the proposed method is compared with the traditional model-driven method.
Photovoltaic charging stations are usually equipped with energy storage equipment to realize energy storage and regulation, improve photovoltaic consumption rate, and obtain economic profits through “low storage and high power generation” .
Our solar power systems and energy storage products are engineered for reliability, safety, and efficient deployment. All systems include comprehensive monitoring and control systems with remote management capabilities.
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