Research on optimal control strategy of wind-solar​ hybrid system based on power prediction

In wind and solar power generation systems, the MPPT algorithm is often used to quantify renewable energy production power, if the light or wind changes suddenly in the algorithm search process, it is possible that the iterative algorithm will not be able to track to the maximum power point or fall into turbulence, and frequent restart of the relevant algorithm will also bring a large energy loss. In view of this situation. For the purpose of further analysis the effect of power output characteristics on the tracking ability of the system, and to enhance the reliability and energy utilization of renewable energy generation system. This manuscript studies an optimal control method for a wind-solar storage complement device designed using power prediction. The article establishes the simulation model of each subsystem separately, and the wavelet packet neural network is used to build a power prediction model. An MPPT optimal control strategy is proposed. This control strategy combines the hysteresis loop comparison-based P&O algorithm in single-peak MPPT and the improved firefly algorithm in multi peak MPPT. The dynamic tracking ability, speed and single peak value and multi peak optimization capability of the algorithm are guaranteed. And the simulation analysis of the control strategy is executed by MATLAB, and the findings demonstrate the efficacy of the optimum control technique proposed in this article. This algorithm has also been shown to outperform traditional intelligent algorithms in terms of tracking efficiency and stability.