Quantification of Uncertainty in District Heating System with Renewable Energy Access

The district heating system(DHS) could realize the flexible consumption of renewable energy by coordinating renewable energy and traditional energy. However, the connection of renewable energy to the district heating system changes its end energy balance. Still, the fluctuation of energy source output and the heat load needs to be considered in the consumption process. We propose a dynamic heat network model and apply Gram-Chalier A(GCA) Series algorithm that enables us to quantify the uncertainty in DHS at both source and load sides. The dynamic model of the heat network is used to characterize the dynamic process inside the DHS. GCA algorithm is used to calculate the probability density semi-analytical formula of the node thermal power. Based on this, the fluctuation interval of node thermal power is calculated by quantile and Bayesian credible interval methods. Study cases show that the proposed models and applied algorithm can effectively calculate the fluctuation interval of the node’s thermal power at both ends of the source and load of the DHS.