区域供热系统是协调可再生能源与传统能源并实现可再生能源灵活消纳的重要载体之一。考虑到可再生能源出力和用户集群热负荷的不确定性对区域供热网络动态输运过程带来的影响，需对源荷双侧的不确定变量和热网的动态特性进行量化分析。本文首先建立了热网的动态输运模型求解其热量损耗和传输延迟特性，其次应用Gram-Chalier A 算法计算系统源荷双侧节点热功率的概率分布半解析式，并采用贝叶斯可信推断计算节点热功率的概率区间。本文选取北京市某二级热网进行模型精度验证与案例分析，该系统拥有90 个节点和109 个管道，结果表明所提出的模型和所应用的算法能有效量化计算热网节点热功率的波动区间。

District heating system is one of the important carriers for coordinating renewable energy and traditional energy and realizing flexible consumption of renewable energy. Considering the impact of the uncertainty of renewable energy output and user cluster heat load on the dynamic transportation process of district heating network, it is necessary to quantitatively analyze the uncertain variables on both sides of the source and load and the dynamic characteristics of the heating network. This paper first established a dynamic transportation model of the heating network to solve its heat loss and transmission delay characteristics. Secondly, the Gram-Chalier A algorithm was applied to calculate the probability distribution semi-analytical expression of the thermal power of the source and load nodes of the system, and Bayesian credible inference method was used to calculate the fluctuation interval of node thermal power. This paper selected a secondary heating network in Beijing for model accuracy validation and case analysis. The system has 90 nodes and 109 pipes. The results show that the proposed model and algorithm can effectively quantify the fluctuation interval of nodes’ thermal power.