Topology optimization method of district heating system considering load uncertainty

With the implementation of the carbon peaking and carbon neutrality strategy, China's heating system has witnessed various transformative trends, including source-network-load integration and the synergistic utilization of fossil and renewable energy sources. The district heating system, serving as a vital intermediary between heat sources and end-users, plays a crucial role in ensuring a stable energy supply. Particularly, as renewable energy integration increases and end-user requirements become more refined, the demand-supply matching aspect of district heating systems becomes increasingly critical. Therefore, it is essential to quantify and analyze user demand while establishing an adaptive pipe network capable of accommodating fluctuations in end-user load. This paper proposes an optimal topology structure method for district heating systems, taking into account the uncertainty of end-user load. Specifically, a quantitative model of end-user load uncertainty is developed, utilizing the Gram-Charlier A expansion method to capture the factors influencing end-user load uncertainty comprehensively. Furthermore, an optimization model for the pipe network topology is formulated, which considers the uncertainty of end-user load as a constraint and aims to minimize pipeline construction costs. This model optimizes the layout, size, and location of heating sources within the district heating system. The proposed method's practical applicability is validated through a case study of a district heating system in a northern Chinese city that involves 21 end-users. The results indicate that the end-user load uncertainty model outperforms the conventional normal distribution fitting model when dealing with bimodal load distributions. Additionally, the proposed method reduces construction costs by 6.24%, decreases heat loss by 5.30%, and eliminates redundant structures within the district heating system. This research significantly contributes to the planning and design of heating pipeline networks and the optimization and refurbishment of existing pipeline networks within district heating systems.