Issue |
E3S Web of Conf.
Volume 410, 2023
XXVI International Scientific Conference “Construction the Formation of Living Environment” (FORM-2023)
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Article Number | 04009 | |
Number of page(s) | 10 | |
Section | Sustainable Engineering | |
DOI | https://doi.org/10.1051/e3sconf/202341004009 | |
Published online | 09 August 2023 |
Identification of parameters of heat supply facilities using telemetry data
Moscow State University of Civil Engineering, Yaroslavskoye shosse, 26, Moscow, 129337, Russia
* Corresponding author: KitaytsevaEH@mgsu.ru
The purpose of the study is to test the hypothesis about the possibility of using telemetry data to identify heat supply objects. The article considers 4 models approximating telemetry data. Determination coefficients and standard deviations were used to select the best model. The residuals were analyzed for randomness, and the absence of shifts and trends. The consistency of the frequency distribution of the residuals with the normal distribution was checked. The significance of the coefficients included in the approximating functions is estimated. Regression analysis was used to obtain the coefficients of 4 models for each of the 7 objects. The Pearson test confirmed the consistency of the distribution of the residuals of one of the models with a normal distribution for all objects. The significance of the coefficients included in all models was confirmed using Student’s t-distribution. The proposed models take into account the flow rate of the coolant and the temperature of the outside air. The dependences obtained do not contradict the physics of the process, both in the field of observation and beyond its boundaries. With certain restrictions on the coefficients of the model, it is possible to obtain numerical values of the parameters of heat supply objects - the average temperature of the indoor air and the required heating load, which confirms the hypothesis that telemetry data can be used to identify the parameters of heat supply objects.
Key words: heat supply facilities / parameter identification / regression analysis / telemetry data
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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