To address the issues of large active power fluctuations and low tracking accuracy in traditional wind and solar hybrid energy stations

leveraging the fast response speed and low adjustment cost of photovoltaic (PV) systems

this paper proposes an optimized control strategy based on real- time PV compensation. Firstly

the maximum achievable active power of the station is calculated. An Adaptive Exponential Moving Average (AEMA) algorithm is employed to process the theoretical power

enhancing the confidence level of the maximum achievable active power and reducing the fluctuation in the station's active power. Secondly

optimize the instruction computing module. By controlling the active power of the PV subsystem

and based on the time- misalignment and stepwise adjustment of wind and PV commands

the power deviation required for the tracking and scheduling commands of the wind and solar hybrid energy station is compensated in real- time. Finally

The strategy was tested on- site at wind and solar hybrid power stations. The results show that the proposed control strategy improves the station's regulation accuracy and reduces active power fluctuations compared to conventional strategies

and has broad application prospects.