A diagnostic approach for fault detection and identification in district heating networks

Manservigi, Lucrezia; Bahlawan, Hilal; Losi, Enzo; Morini, Mirko; Spina, Pier Ruggero; Venturini, Mauro

doi:10.1016/j.energy.2022.123988

Cited by 20 publications

(12 citation statements)

References 54 publications

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“…As outlined in [8] and [9], the efficiency of DHNs depends on pipe health state, which can be compromised by three fault types, i.e., leakages, anomalous heat and pressure losses. Water leakages are caused by pipe corrosion [10] and failures in welded joints.…”

Section: Introductionmentioning

confidence: 99%

“…In the literature, only a few diagnostic methodologies tackled this goal, by simultaneously detecting water leakages along pipes, and anomalous heat and pressure losses. This purpose has been recently pursued by Manservigi et al [8] and Bahlawan et al [9], who developed a novel diagnostic approach for detecting and identifying faults affecting DHN pipes. In [8] and [9], the DHN diagnosis was performed by coupling a DHN simulation model with an optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…This purpose has been recently pursued by Manservigi et al [8] and Bahlawan et al [9], who developed a novel diagnostic approach for detecting and identifying faults affecting DHN pipes. In [8] and [9], the DHN diagnosis was performed by coupling a DHN simulation model with an optimization algorithm. The DHN simulation model calculated the DHN variables, i.e., mass flow rate, temperature and pressure at each pipe and node of the DHN, while the optimization algorithm identified pipe health indices in such a manner that the error between measurement and simulated variables was minimized.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, Manservigi et al [8] investigated the effect of different fault magnitudes on the DHN variables. Subsequently, the diagnostic methodology was challenged at detecting and identifying faults affecting the DHN of the campus of the University of Parma.…”

Section: Introductionmentioning

confidence: 99%

“…In the current paper, the diagnostic approach developed and validated in [8] and [9] is further tested by means of two additional case studies simulated by means of the digital twin [9]. In the first dataset considered in this paper, one pipe is affected by anomalous pressure losses due to two simultaneous fault causes, i.e., increase in pipe roughness and decrease in pipe internal diameter.…”

Section: Introductionmentioning

confidence: 99%

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Fault diagnosis in district heating networks

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J. Phys.: Conf. Ser.

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District Heating Networks (DHNs), which dispatch thermal energy from a heat source to end-users by means of a heat carrier, are composed of pipes that can be affected by faults that endanger system reliability. Thus, reliable diagnostic approaches have to be employed to evaluate the health state of the DHN. In the framework of the ENERGYNIUS research project, the authors of this paper developed a diagnostic approach aimed at detecting and identifying the most frequent faults that affect DHN pipes, i.e., water leakages, heat losses and pressure losses. The diagnostic approach detects and identifies pipe faults by coupling a DHN model with an optimization algorithm. As a result, the health indices of each pipe of the DHN, the fault position, its type and magnitude are provided. This study investigates the capability of the diagnostic approach by using two datasets, in which challenging faults were hypothetically implanted in the DHN of the campus of the University of Parma. The diagnostic approach successfully detected and identified both faults, by also accurately assessing fault magnitude. In addition, the relative error with which each DHN variable is predicted is lower than 0.06 %.

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Section: Introductionmentioning

confidence: 99%