Under large-scale wind and photovoltaic (PV) power grid integration

on the one hand

a large number of pumped storage power stations are needed to reduce the peak-to-valley difference of the power grid and alleviate the climbing pressure of other regulating power sources. On the other hand

it is also necessary to smooth the uncertainty of wind and PV power output. However

due to the limited storage capacity of pure pumped storage stations

if there is a large deviation in the wind and PV forecast for multiple consecutive periods

the adjustment storage capacity will be insufficient. Therefore

developing a reliable plan for pumped storage to manage wind and PV prediction errors is key to building a new power system. This paper uses the Gaussian Mixture Module to describe the forecast cumulative error of wind and PV power output

explores the upper and lower deviation electricity

and uses this as the boundary condition of reserve electricity to limit the operation mode of four hypothetical variable-speed pumped storage power stations in a province in short-term scheduling. Using the mixed integer linear programming algorithm

the results show that the proposed model method can effectively solve the problem of power consumption of variable speed pumped storage power station under the continuous accumulation deviation of wind and PV output. Meanwhile

the model can reduce the peak-to-valley difference of the remaining load of the power grid by more than 80%.