Automatic fouling detection in district heating substations: Methodology and tests
Elisa Guelpa and
Vittorio Verda
Applied Energy, 2020, vol. 258, issue C
Abstract:
Diagnosis of anomalies in heat exchangers of district heating substations is an essential point to assure high comfort level in buildings, as well as to exploit energy sources efficiently. The aim of this paper is to propose a methodology for automatically detecting fouling in the heat exchangers located in the substations of a district heating system. The methodology is tailored for large district heating networks, where a large number of buildings should be examined with reasonable availability of data. Fouling is analysed using only the data collected by the meters installed in the substations: the mass flow rate on the primary side and the temperatures on both sides of the heat exchanger. Evaluation is difficult due to the rawness of the data gathered and the variable operating conditions, which are adjusted on the basis of the external temperatures and set-points. The software created to implement the proposed methodology receives rough data as the input and it is able to manage data gap and lack of data. Furthermore, it provides a graphical output, which can be used for assisting the operators who manage the network and plan the cleaning schedules. The software has been tested considering space heating substations in six distribution networks of the Turin district heating system, for a total amount of 325 heat exchangers. A regular application of the approach and the cleaning of the heat exchangers presenting fouling is expected to lead to an average annual decrease of about 1.6% of the primary energy consumption in the entire network.
Keywords: Smart thermal grids; Sustainable energy systems; Heat exchanger; Malfunction detection; 4GDH (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (9)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:258:y:2020:i:c:s0306261919317465
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DOI: 10.1016/j.apenergy.2019.114059
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