Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN

Due to strong volatility and intermittent characteristics, the fluctuations of the photovoltaic (PV) output is inevitable which cause negative impacts on power system operation. However, such an issue can be resolved in a combined cascade hydro-PV-pumped storage (CH-PV-PS) generation system through an appropriate control. Based on the optimal base power of variable-speed pumped storage station (VSPSS), a smoothing method of fuzzy complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is proposed in this paper. To prevent smoothing insufficient and excessive, the fuzzy CEEMDAN algorithm is used to obtain the target power of the photovoltaic-pumped storage (PV-PS) generation system and the control signal of cascade hydro stations (CHSs) for eliminating large amplitude fluctuations of the PV output. Furthermore, in order to overcome the drawback that too frequent conversion of unit operating mode would reduce the service life and smoothing effect of the VSPSS unit, the optimization model of the base power of the VSPSS is established and solved by the grid adaptive direct search method (MADS) to obtain the control signal of the VSPSS for suppressing the short-term fluctuations of the PV output. Finally, the performance of the method is evaluated through using the PV station data in Xiaojin County, Sichuan province, China. The simulation results reveal that compared with the fixed base power smoothing method, this method can effectively suppress the PV power fluctuations and improve the smoothing effect and energy efficiency.