E3S Web Conf.
Volume 39, 2018Mathematical Models and Methods of the Analysis and Optimal Synthesis of the Developing Pipeline and Hydraulic Systems
|Number of page(s)||6|
|Section||Control of Functioning of Pipeline Systems|
|Published online||26 June 2018|
Regression model for heat consumption monitoring and forecasting
Melentiev Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences (ESI SB RAS), Pipeline Energy Systems Department, 130, Lermontov str., Irkutsk, Russia, 664033
† Corresponding author: email@example.com
Heat supply is socially and economically important in our country. In this regard, high-quality monitoring and planning of the development of heat supply systems are a strategic vector of scientific research. This paper is focused on the studies demonstrating how to choose a methodological approach to describe changes in heat consumption in the retrospective. The change in heat consumption is described using multiple regression models. In the first part of the paper, the parameters for the regression model are determined and a statistical analysis of the obtained model is performed. In the second part of the paper, to eliminate the multicollinearity of the regression equation, the number of dependent variables in the model is reduced. A statistical analysis of the new regression model and the exponential regression model are carried out. The heat consumption values obtained using these models are compared with the statistical data. The conclusions about the quality of the obtained regression models are made. In the third part of the article, we make a forecast of heat consumption in the medium term by using a linear regression model and an exponential model.
© The Authors, published by EDP Sciences 2018
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. (http://creativecommons.org/licenses/by/4.0/).
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