Monitoring in a District Heating Pipeline System

Villalobos, Felipe; Hay, Stuart; Weidlich, Ingo

doi:10.1007/978-3-319-99670-7_17

Cited by 2 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pressure sensors are installed in the network, and the data are permanently recorded [2]. With a monitoring program, the data can also be used to assist operator actions in the case of certain events [3]. If a leakage occurs, it is associated both with the loss of transport medium and with an initially local change in pressure conditions (a pressure drop).…”

Section: Introductionmentioning

confidence: 99%

Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data

et al. 2022

View full text Add to dashboard Cite

Leakages can occur in a district heating network, resulting in high economical damage. The propagating pressure wave resulting from large, spontaneous leakages reaches sensors at different locations in the network. This leads to pressure drops registered at each sensor at a different point in time. The time differences help to localize the leakage. Different algorithms are presented and applied in this paper to estimate the pressure drop time points based on non-uniform, time-discrete sensor signals. Five of the nine algorithms are self-developed with, e.g., parts of linear regression, whereas the other four algorithms have already been described in the literature, such as change-point detection. In this paper, several recorded events were investigated, and the algorithms were applied to real measurement data. After detection, leakage localization was performed to determine the affected exclusion area. A performance criterion was used as a measure to compare the algorithms. For practical application, the best-performing algorithm was identified. Furthermore, the events were classified according to how well they could be evaluated.

show abstract

Section: Introductionmentioning

confidence: 99%

Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data

et al. 2022

View full text Add to dashboard Cite

show abstract

“…An uninterrupted energy supply is required. However, there is a risk of leakages because the hot fluid medium is transported under high levels of pressure [ 2 ]. In Figure 1 , a schematic representation of a DHN is shown.…”

Section: Introductionmentioning

confidence: 99%

Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization

Vahldiek

Rüger

Klawonn

2022

Sensors

View full text Add to dashboard Cite

Large spontaneous leakages in district heating networks (DHNs) require a separation of the affected network part, as interruption of the heat supply is imminent. Measurement data of 22 real events was analyzed for localization, but suitable results were not always achieved. In this paper, the reasons are investigated and a model for data evaluation (MoFoDatEv) is developed for further insights. This contains prior knowledge and a simplified physical model for the reaction of the DHN in the case of a large spontaneous leakage. A model like this does not exist so far. It determines the time point and the duration of the pressure drop of the pressure wave which is caused by such leakages. Both parameters and the evaluation time frame are optimized for each event separately. The quality assessment leads to a categorization of the events based on several parameters, and correlations between the pressure and the refill mass flow are found. A minimum leakage size is deduced for successful evaluation. Furthermore, MoFoDatEv can also be used for leakage localization directly, combining two steps from previous publications. Therefore, more data contribute to the result. The application is conducted with artificial data to prove the model concept, and also with real measurement data.

show abstract

Monitoring in a District Heating Pipeline System

Cited by 2 publications

References 3 publications

Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data

Application and Optimization of Algorithms for Pressure Wave Evaluation Based on Measurement Data

Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization

Contact Info

Product

Resources

About