The growth of construction projects increases the demand for mobile energy storage systems. Therefore, mobile energy transport systems are essential for limiting carbon emissions in road traffic. This paper proposes a model for optimizing the MESS transportation route. Considering many operating restrictions, the model is designed to reduce operating costs, thereby improving the efficiency of transport management for construction sites. The mixed integer linear programming technique is used to develop the model and is implemented using Python. The model was first solved by the PuLP package, which employs the CBC solver. Subsequent improvements included dynamic programming techniques to enhance the model’s ability to adapt to changing operating limitations. This method is designed to dynamically update the MESS’s state of charge and adjust the pickup decisions accordingly. Validation in several scenarios has confirmed that the methodology significantly reduces travel lengths and operational expenses, enabling more sustainable MESS transportation in the construction sector.