Large-scale integration of wind power and solar power has led to highly fluctuating residual loads on the power systems

posing a great challenge to the short-term operation of pumped storage stations. This study focuses on a real case of the Heimifeng pumped storage station that connects to the Hunan power grid in Central China. Based on previous studies of residual load forecasting

we develop a short-term model for optimal operation of the station

incorporating multi-period operational constraints. This model considers dual objectives－maximizing power generation benefit and minimizing residual load fluctuations; it is equipped with an improved genetic algorithm for efficient solution

applicable to the cases of complicated constraints－including operational mode transitions and reservoir water balance. Results demonstrate that with the forecasted typical residual load sequences used as input

the optimized operation achieves an average daily power generation benefit of 1.5254 million Yuan

or an increase of 36% relative to the existing real operation

while reducing residual load fluctuations by 34%. This study is practically useful for economical operation of a pumped storage station

and helps enhance grid flexibility under high penetration of renewable energy integration.