Component-level fault diagnosis in district heating networks by using a physics-based approach

A District Heating Network (DHN) is composed of several components that may be prone to faults; therefore, diagnostic tools are necessary to identify malfunctions that reduce system efficiency. This study presents a physics-based diagnostic tool for the detection and identification of faults in the key DHN components, namely, pumps, pipes, valves and heat exchangers. Fault detection involves locating the faulty component, whereas fault identification enables the estimation of fault signature as well as its magnitude. The proposed diagnostic tool relies on a physics-based model of the DHN. The governing equations include the variables (namely, health indices and valve opening) that are useful to assess the health state of each DHN component (i.e., healthy or faulty condition, and fault magnitude). The values of such variables are identified by means of an optimization algorithm. The DHN serving the Campus of the University of Parma (Italy) is used as a case study. Its operation is reproduced by means of a reliable data simulator in both healthy and faulty conditions. The results demonstrate that the proposed diagnostic tool accurately evaluates the health state of all DHN components, i.e., both fault detection and fault signature are correctly identified. In addition, the difference between the actual and calculated fault magnitude is negligible in most cases, proving that the health state of each DHN component is always reliably estimated. Its reliability, computational efficiency, and robustness to noise make the diagnostic tool suitable for real-world applications.