The current reefer container ship controls the refrigerated containers individually, such mechanism lacks of unified dispatch management of the refrigerators. The power demand of single refrigerator is random, resulting in large peak-valley difference of the total electric power demand, which further affects the power allocation and efficiency of ship power station. In order to solve the above problems, a reasonable dispatch of the refrigerated containers should be carried out with the prerequisite of ensuring the safety of temperature. This study proposes a scheduling algorithm based on quantum genetic algorithm for power balancing to find the optimal scheduling strategy for refrigerated containers. Firstly, this study establishes a mathematical model for the optimal scheduling of refrigerated containers, determining the optimization targets and constraint conditions. Secondly, it uses the Genetic Algorithm (GA) and Quantum GA (QGA) to solve the objective function, followed the comparison of their actual power changes before and after the scheduling and evaluation of the optimal scheduling capability of the two algorithms. The experimental results show that both QGA and GA can realize the optimal scheduling of refrigerated containers and reduce the peak-valley difference of total power demand, thus balance the power load. Nevertheless, QGA converges faster than GA, and its ability is stronger than that of QA in terms of balancing power demand and optimizing power station.