The development of Digital Twin Technology, with a focus on addressing environmental concerns, has elevated the priority of Industry 4.0-based solutions. The study aimed to design a simulation model to optimize the electricity consumption of the electric bus fleet at Arlanda Airport as a subproject of the main Digital Twin project. The study found that there was no current model designed to simulate electricity consumption by formal methods, Z notation.  The research is guided by four primary objectives find power management strategies for e-buses, identify critical parameters affecting their energy consumption, create a Z Notation simulation model, and assess this model. Through a thorough review of the literature and methodical application, power management strategies were defined, and significant energy consumption parameters were identified. The model's usefulness in modelling and optimizing electricity usage was demonstrated by its careful construction using Z Notation and evaluation with Spivey's Fuzz Checker. The paper demonstrates the use of Design Science Research in creating a digital twin-based simulation, which has important implications for transportation systems as well as theoretical advances in simulation methodologies. Throughout the developed Z notations, it provide a proper insight into operational efficiency and sustainability in energy consumption.  The study also emphasizes the drawbacks of using Z Notation, such as its steep learning curve and limited community assistance. To improve the accuracy of electricity consumption forecasts, future research should use predictive analytics and fine-tune the model granularity. The thesis demonstrates how design science can be applied for preparing specification of services but not only in software development. This work lays the groundwork for more extensive applications in digital twin technologies and energy optimization, in addition to contributing to our understanding of e-bus power management at Arlanda Airport.