Abstract: The renewable energy and storage configuration of port microgrid is closely related to its production schedule and berthing ships. Hence, it is difficult to accurately describe the system operation characteristics by determining the time scale of scene according to the natural law. This paper proposes a high-fidelity compression and refactoring method for port microgrid operation scenarios. It can dynamically adjust the time scale of each operating point according to the operation state, and describe the renewable energy and load power characteristics in fidelity while effectively compressing the data scale. The representative operating weeks are obtained according to the similarity between operating weeks through hierarchical clustering. Then the consecutive hierarchical clustering method is proposed to dynamically adjust the time scale of each operating point according to the similarity between adjacent moments and realize the data refactoring. An optimal renewable energy and storage configuration model with adjustable time scale is also established, and the model is linearized by convex relaxation. Finally, taking Rizhao Port as an example, when the compression rate of the operation scenarios is 1.92%, the error between the total cost of the renewable energy and storage configuration obtained by the proposed method and the full-data method is only 0.6%. The accuracy is improved by more than 6% compared to other existing methods.