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.
Secondly, to minimize the investment and annual operational and maintenance costs of the photovoltaic–energy storage system, an optimal capacity allocation model for photovoltaic and storage is established, which serves as the foundation for the two-layer operation optimization model.
The operation schemes of the photovoltaic system and energy storage in the lower layer model utilize the upper layer optimization results as a reference point, correcting for any deviations in the system state due to uncertainty factors.
It is a rational decision for users to plan their capacity and adjust their power consumption strategy to improve their revenue by installing PV–energy storage systems. PV power generation systems typically exhibit two operational modes: grid-connected and off-grid .
Optimizing the energy storage charging and discharging strategy is conducive to improving the economy of the integrated operation of photovoltaic-storage charging. The existing
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