In the water and wastewater treatment system, household wastewater is discharged through drainage pipes and enters the municipal sewer system by gravity. The wastewater flows downward until it reaches a point lower than the sewer network, where it can no longer move by gravity. A pumping station is installed at this low point so that the wastewater can be pumped to a higher elevation, allowing it to flow again through the sewer network and be transferred to wastewater treatment plants. In recent years, with population growth and increased water consumption, the design, construction, and operation of pumping stations have faced more complex challenges. In a pumping station, the most important factor is the operation of the pumps. Since the efficiency of a pump varies with its discharge, the amount of energy consumed by each pump also differs for different pumping flow rates. Therefore, pumps should operate at their maximum efficiency whenever possible. With the presence of multiple pumps in the system, achieving optimal system performance requires proper scheduling. This approach works well in pipelines with high friction losses, and if a pump operates for a longer period at optimal speed and discharge, compared to operating at a constant speed, energy consumption will also be reduced.Optimizing the design and operation of a pumping station leads to effective energy management and conservation. This paper determined the energy consumption of pumps in a wastewater pumping station in the city of Mashhad, under a recurring pattern of inflow rates. Using a gray wolf optimization model, the variable pumping speed for a two-pump station was established, and the on-off sequence of the pumps during summer was determined for various speed and flow rate variation coefficients, then compared with the fixed speed scenario. The Gray Wolf Algorithm has a higher speed compared to other algorithms due to dividing the population into smaller groups. It has also been improved through the linear combination of group positions, which leads to better convergence and the achievement of the most optimal position. Moreover, it demonstrates better performance than other algorithms when dealing with scattered and complex problems. The optimal values for flow rate, pump speed, pump power, and consequently pump efficiency were calculated, and the pump performance was analyzed using three different indices: standard reliability, Monte Carlo, and moment method. The energy consumption at a lower variable speed was reduced compared to the classical approach. By employing the optimized variable speed, energy savings of over 70% can be achieved. The results clearly show that the efficiency of the system can be maintained over many years through an optimal scheduling of pump operation. The standard reliability index, ranging from 0.75 to 0.95, indicates that both pumps maintain good operational reliability across various flow parameters. The results from the Monte Carlo simulation show values around 0.61. The moment method indices vary between 0.58 and 0.8, providing a more precise evaluation that considers the magnitude and distribution of operational deviations, and these values correlate well with the results from the standard reliability index.