To achieve dual carbon goals, the photovoltaic-energy storage-charging integrated energy station attracts more and more attention in recent years. By combining various energy sources like solar, wind, and battery storage, these stations can ensure a stable and sustainable energy supply. With the proper energy management of the integrated energy station, it can contribute to reducing carbon emissions, enhancing operation profit, and promoting the transition towards clean energy. This paper considers this optimal energy management problem. The following contributions are made. First, an optimal energy management model is proposed under the Model Predictive Control (MPC) framework considering the charging control of EVs and the uncertain supply. Second, a Grey Wolf Optimization (GWO) is proposed to solve this non-linear multi-stage optimization problem. In order to speed up the optimization process, an Ordinal Optimization (OO) mechanism is incorporated to select the wolves with good enough performance. Numerical experiments demonstrate the operation profit of the integrated energy station can be enhanced and the proposed method has a faster convergence speed than the traditional GWO method.