Lessons Learnt from Substation Inspection on Low Temperature District Heating Networks †
Abstract
:1. Introduction
2. Materials and Methods
2.1. Primary Side Temperatures (T1 and T2)
2.2. Secondary Side Temperatures (T3 and T4)
2.3. Domestic Hot Water (T5)
3. Lessons Learnt
- Data monitoring is an essential tool for DH optimization, but it is time consuming to analyze large sets of data in a traditional way.
- The automatization of data analysis is beneficial to improve the operation of the DH, allowing issues to be identified in real time.
- Automatic data analysis can be performed at a low computational cost. One year of hourly data from 54 substations were analyzed, along with the consequent production of warnings generated upon sub-optimal behavior, in less than 10 min with a laptop.
- Large DH operators often lack this kind of service, instead focusing on the analysis of the biggest consumers to optimize the service or being reactive to consumer complaints. A proactive approach to further optimize DH operation has yet to be exploited.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Garrido-Marijuan, A.; Eguiarte, O.; Garay-Martinez, R.; Raud, M.; Hagu, I. Lessons Learnt from Substation Inspection on Low Temperature District Heating Networks. Environ. Sci. Proc. 2021, 11, 33. https://doi.org/10.3390/environsciproc2021011033
Garrido-Marijuan A, Eguiarte O, Garay-Martinez R, Raud M, Hagu I. Lessons Learnt from Substation Inspection on Low Temperature District Heating Networks. Environmental Sciences Proceedings. 2021; 11(1):33. https://doi.org/10.3390/environsciproc2021011033
Chicago/Turabian StyleGarrido-Marijuan, Antonio, Olaia Eguiarte, Roberto Garay-Martinez, Margus Raud, and Indrek Hagu. 2021. "Lessons Learnt from Substation Inspection on Low Temperature District Heating Networks" Environmental Sciences Proceedings 11, no. 1: 33. https://doi.org/10.3390/environsciproc2021011033