###### Abstract
Compared to conventional cascade hydropower stations, the cascade hybrid pumped storage plant transitions from a single \"peak shaving\" mode to an integrated mode of both \"peak shaving\" and \"valley filling\", where peak shaving refers to increasing electricity generation during peak demand periods to avoid grid overload and ensure supply meets demand, while valley filling involves storing excess energy during off-peak periods (typically at night or when renewable generation like PV is abundant) so that it can be released during peak demand periods [8]. This integrated mode enhances the regulation capacity during low-demand periods, thus efficiently balancing supply and demand. 3. Compared to traditional pure pumped storage plants, the cascade hybrid pumped storage plant benefits from water inflow from upstream hydropower stations, so its generation is no longer limited by the circulating water volume between the upper and lower reservoirs. This allows for increased output during peak electricity price periods, resulting in higher generation revenue [9]. Therefore, if eligible cascade small hydropower stations can be converted into cascade hybrid pumped storage plants, utilizing the storage function of their reservoirs to effectively integrate cascade small hydropower with distributed wind and PV, it can enhance the stability and economy of the regional power system. Reasonably configuring the capacity of pumped storage units and various renewable energy sources is key to achieving the effective integration of cascade small hydropower, pumped hydro storage, and distributed wind and PV resources. The capacity configuration issues in multi-energy complementary systems can be roughly divided into two categories. One analyzes system costs to calculate the optimal capacity configuration scheme to maximize economic benefits. References [10; 11; 12] aim to minimize annual operation and maintenance costs. In Reference [13], the Bloch spherical quantum genetic algorithm was used to establish the objective function with the minimum cost of the energy storage system as the goal, and the capacity value required for the configuration was solved. Reference [14] studied how different economic sensitivity factors affect the configuration results to optimize the energy storage system configuration scheme. The other focuses on analyzing the fluctuation characteristics of wind and PV output power and determining the optimal capacity allocation under the prerequisite of meeting a predefined fluctuation smoothing requirement. Reference [15] proposes the Ramping Behavior Analysis (RBA0) model, which extracts the temporal characteristics and magnitude of wind ramp events, providing technical support for the management and scheduling of wind power variability. By forecasting wind power fluctuations, the system can optimize energy storage capacity in advance, reduce the impact of uncertainty, and ensure stable operation of the power system. Reference [16] applies the Fast Fourier Transform and wavelet packet methods to process the amplitude of grid-connected wind power. Low-frequency components with smaller fluctuation rates are integrated into the grid, while high-frequency signals are characterized using Gaussian distribution to obtain their probability density curves. Finally, capacity optimization is carried out based on a confidence level reference. Reference [17] adopts a spectral analysis method to process typical daily output data of distributed energy sources. By performing rolling calculations, the expected output under the optimal cut-off frequency is obtained, which is then used to determine the capacity configuration of the distributed energy system. Reference [18] employs an adaptive wavelet packet method to process wind power output and allocates internal energy storage power based on control instructions. The annual cost is used as the evaluation criterion to determine different instruction segmentation points, and the optimal segmentation point is identified to obtain the final capacity configuration.