Methods of monitoring, analysis and short-term prognosis of gas consumption taking into consideration its cyclic and non-stationary structure in heating season

Zagorodna, Natalia; Kozak, Ruslan; Gancarczyk, Tomasz; Fałat, Paweł

doi:10.1109/iccas.2016.7832366

Cited by 1 publication

(1 citation statement)

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“…Consider the known approaches to forecasting gas consumption and analysis of their models. In [1,2] the method of short-term forecast is described, which makes it possible to analyse and calculate the predicted values of gas consumption in the heating season, taking into account its cyclicity and ambient temperature. There are also approaches to forecasting natural gas consumption using a system of fuzzy conclusions based on the adaptive network (ANFIS) [3].…”

Section: Analysis Of Recent Researchmentioning

confidence: 99%

Method of Evaluation of Discrete Rhythm Structure of Cyclic Signals with the Help of Adaptive Interpolation

Lytvynenko

Lupenko

Onyskiv

2020

2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT)

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In the article, the approach to gas consumption process prediction on the basis of a mathematical model in the form of a cyclic random process is considered. The prediction is based on statistical information for previous years of gas consumption. An additive combination of three components was used as a mathematical model of gas consumption process: a cyclic random process, a trend component and a stochastic residue. The first component of the mathematical model in the form of a cyclic random process takes into account the scale factors, information about which is considered at the stage of prediction. Based on the caterpillar decomposition, ten components of the singular decomposition are obtained. The sum of nine components of singular decomposition forms a cyclic componenta cyclic random process. This component takes into account the scale factors of the amplitude of gas consumption process in each segment-cycle. The trend component of the mathematical model is the second component of the singular decomposition, and the stochastic residue is formed on the basis of the difference between the values of the studied gas consumption process and the sum of the cyclic and trend components. Computer simulation of realization of cyclic component of gas consumption process is carried out in the work, and also the annual forecast of gas consumption is made. The prediction results are compared with the real gas consumption process (information for last year's gas consumption was used). This paper does not take into account the effects of climatic conditions on the gas consumption process, but this is going to be done in further research, which will improve the accuracy of computer simulation and prediction.

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Section: Analysis Of Recent Researchmentioning

confidence: 99%