Heat Loss Determination of District Heating Pipelines. A Comparison of Numerical and Analytical Methods - Wieland Aaron; Dollhopf Stefan; Weidlich Ingo; Langroudi Pakdad Pourbozorgi (Environmental and Climate Technologies)
Assessing the energy efficiency of district heating systems considers the network heat losses. For example, life cycle assessments of engineering structures like these necessitate an understanding of heat losses incurred during their operational phase. Therefore, it is essential to know the heat losses of district heating pipelines with the utmost accuracy. In this study, three different methods for determining specific heat losses for buried pre-insulated steel pipes are compared. The first method involves an analytical calculation in accordance with EN 13941, while the second utilizes an equivalent mesh current approach. The third method employs finite element analysis. The objective was to evaluate the accuracy of the methods, the achievable range of results, and the possible input parameters. Therefore, typical 2-dimensional cross sections including different pipe diameters were selected. In situ measurements were not part of this study. Consequently, the analysis centres on the deviation between the methods. All three methods determine the heat loss in both the supply and return pipes. While the analytical calculation method does not consider multiple soil layers, the equivalent mesh current method can handle more complex tasks and gives detailed results at predefined points in the system. With the finite element method, a high degree of detail can be achieved, but the number of input parameters for solving the algorithms increases. An emerging trend in district heating involves reducing operational temperatures in both new and existing networks. This will change the relation between heat losses and heat delivered to the customers. Subsequently, an increasing interest in the actual heat losses and the precision of calculation is expected within this development. Therefore, it remains essential to evaluate the performance of different models.