## 1 Introduction
It also performed reliability evaluations at different time periods. The above references have laid a solid basis for the reliability evaluation method of multi-energy supply in this study. However, the coupling characteristics of multi-energy and the simulation of time scale remain insufficient. One of the goals of reliability evaluation is to provide the corresponding guidance for the reasonable planning of the system, and an effective and reasonable planning method lays a solid foundation for the construction of the energy Internet in the future. At present, there is a certain research foundation for the collaborative planning method of a multi-energy network. In terms of planning methods, Reference [17], e.g., assessed the impact of different equipment configuration schemes on the reliability and economical performances of integrated microgrid systems. However, this study has only conducted concrete research on the electric power microgrid. Reference [18] proposed a multi-energy system planning method and analyzed the impact of a reliability constraint on the selection of system planning schemes. However, the paper took the simple index as the reliability constraint without systematically introducing the multi-energy comprehensive reliability evaluation method. Reference [19] took Masirah Island in Oman as an example to analyze the technical and economic viability of a hybrid energy system; different scenarios were established based on different configurations of equipment. On this basis, the impacts of different scenarios were considered in the hybrid system optimization. This study laid a solid empirical basis for subsequent planning implementation. In accordance with the principle of the Bayesian filter structure, Reference [20] proposed a state estimation and stabilization algorithm for smart grid and further designed a semidefinite programming-based optimal feedback controller. This study has built a good foundation for further analysis, evaluation, and adjustment of the state of the system. Besides, some references have also studied the expansion planning methods of energy hubs. Reference [21] proposed a planning and configuration method for an energy hub with multiple energy systems, and further assessed the performance of the planning program in terms of energy efficiency and emissions. Despite the wealth of valuable information on this subject, there is much work to be done to ensure the safe and practical application of multi-energy supply systems. The above researchers primarily emphasized the single energy network level represented by electric energy, and neglected the impacts of peak and valley differences in various energy load demands; thus, their results do not reflect the specific requirements for integrated energy synergistic planning. Mathematical analysis methods are usually employed to analyze reliability, whereas these methods do not reflect the characteristics of the unit and user demand in the timing series. Researchers also tend to ignore the respective energy grades of different energy sources, thereby not securing feasible energy supply/storage priority and load reduction strategies. Traditional planning methods are tailored to operation, in which the optimization goal is the minimal comprehensive cost formed by the operation cost, startup cost, and fuel cost of the system; the randomness of unit failure and the reliability of the power system are typically not considered. The economical factors under normal operation as well as any possible risks of the system must be properly accounted in planning the configuration of a multi-energy microgrid. Given the above problems, this study selected a multi-energy microgrid as its research target and employed the energy hub model to analyze the coupling relationship between multi-energy networks. Subsequently, the energy efficiency and economical models of the key equipment in the multi-energy microgrid system were proposed in this study.