###### Abstract  
This paper proposes a new network topology design method that considers all the road nodes, energy stations and load centers to ensure the distribution of pipes along the road. The traditional graph theory and Prim Minimum Spanning Tree (MST) are used to simplify the map and minimize the length of the pipeline. After analyzing the limitations of the traditional network topology model, Point-to-Point (PTP), we present a new model, Energy Station-to-Load Point (ESLP). The model is optimized by minimum cost, not the shortest path. Finally, Pipe Diameter Grading (PDG) is proposed based on ESLP by solving for the pipe diameter that gives the minimum cost under different load demands in the process of optimization. The network design method is effectively applied in a case, and the results show that the path of the optimized plan is 1.88% longer than that of the pre-optimized plan, but the cost is 2.38% lower. The sensitivity analysis shows that the cost of pipeline construction, project life and electricity price all have an impact on the optimization results, and the cost of pipeline construction is the most significant. The difference between the different classifications of pipelines affects whether PDG is effective or not. d 2021 11 1795 10.11.11.11.11.11.11.11.11.11.11.11.11.1.11.1.11.1.11.1.11.1.11.1.1.11.1.11.1.1.1.11.1.1.1.1.1.1.11.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.1.  
economic index, and environmental index as objective functions, and considered social factors, market factors and safety margin as constraint conditions, unfortunately, without a mathematical model to run it [9]. Based on the planning example of a park and the concept of multi-scene planning, [PERSON] and [PERSON] analyzed the subsystem planning of the integrated energy station and the benefits of the multi-energy complementary system [10]. The hybrid integer nonlinear algorithm showed excellent performance in dealing with the optimization of renewable energy system, whose efficiency was low during the voltage recovery process because of the rapid response of the renewable energy system [11]. The planning of a regional integrated energy system based on Combined Cooling, Heating and Power (CCHP) system and heat network was studied, and the planning of capacity optimization of multi-regional CCHP system was analyzed. However, the heat network model based on mixed integer linear programming is so simplified, while ignoring temperature and pressure changes, that it obtained a result that required further discussion [12]. It should be noted that the abovementioned studies only paid attention to the size and location of energy stations in the optimization, without considering the interplay between energy stations and energy transmission networks. The transmission network is also an important part of the district energy system, and has a strong influence on the operational performance of DES [13]. Major factors in the network design include pipeline diameter [14; 15], pipeline topology [16], field heat loss [17], mass flow, and thermal conductivity distribution [18]. A novel methodology involving both kernel density estimation and the shortest path method was proposed to optimize the transmission network [19]. In their study, the transmission path was optimized using an energy distance function [16], but the pipelines were distributed without considering the actual road distribution. The impact of the quantity and layout of the heating network on the carbon footprint of the system was discussed [20]. Based on the energy flow balance constraint and heat network characteristics, the layout planning model of the energy station supply pipeline was established, and the resolution process was simplified using hybrid mutation particle swarm optimization algorithm [21], but the results cannot be proved to be optimal in the process of simplification.