Collaborative optimization design for district distributed energy system based on energy station and pipeline network interactions

District distributed energy systems (DDESs) are widely used worldwide due to their environmentally-friendly and energy-saving characteristics. The strong correlation and coupling of energy stations and pipeline networks lead to difficulties in the collaborative optimization design of the DDES. To minimize the total annual cost of the system, this research proposed a collaborative optimization model to realize the integrated design of the DDES. The energy distance method is combined with the K-means cluster method to solve the problem of locating and sizing energy stations. The pipelines planning algorithm based on "Dijkstra algorithm (DA) + genetic algorithm (GA)" is used to optimize the pipeline layout and diameter simultaneously. The improved DA method continuously updates the cost full adjacency matrix and pipe diameter matrix of each pipe segment by optimizing the access sequence of user nodes, and finally obtains the optimal layout and pipe diameter of the pipe network at the same time. Moreover, this paper reveals the influence factors that should be considered in the planning of DDES, such as the number of energy station and flow velocity. The results indicate that compared to traditional optimization processes, the collaborative method proposed in this paper reduced the total annual cost of the pipeline network by 20.5 %. The improved DA method solves the problem of pipeline sharing while preventing the system from falling into local optima. Moreover, optimizing the number of energy stations and flow velocity can reduce annual cost of pipelines by 0–14 % and 0–20 %, respectively. This study provides theoretical guidance and technical support for researchers in the planning and designing of DDES.