Open AccessSimulation and predictive control of the gas transportation system in a large industrial zone
Author(s) -
Sergey Marchenko,
Leonid Berner,
Yuri M. Zeldin
Publication year - 2021
Publication title -
nexo
Language(s) - English
Resource type - Journals
eISSN - 1995-9516
pISSN - 1818-6742
DOI - 10.5377/nexo.v34i06.13174
Subject(s) - model predictive control , time horizon , cell transmission model , fuel efficiency , control theory (sociology) , supervisory control , control (management) , flow (mathematics) , computer science , control system , process (computing) , gas consumption , discrete time and continuous time , engineering , mathematical optimization , mathematics , statistics , automotive engineering , process engineering , geometry , intersection (aeronautics) , electrical engineering , artificial intelligence , aerospace engineering , operating system
The article describes an approach to the operational and supervisory control of a gas transmission system for large industrial zones using a model predictive control, as well as analytical and simulation methods. The operational and supervisory control of the gas transportation system covers the time horizon from several hours to several days and involves performing several cyclically repeated actions. The authors propose a time series predictive model of the gas consumption parameter considering temperature weather conditions, which is extended based on accounting for the correlation relationships between the consumption volumes of each consumer. The control methods used today, reacting to the current deviations from the planned regime, a priori do not allow achieving the best results. A significant increase in the stability of control and a reduction in the cost of fuel and energy resources can be achieved by using the control method based on predictive models. In this case, the control object model is used to predict its behavior within the selected time horizon, and optimal control actions are selected on this basis. The process of predicting and selecting control actions is periodically repeated, constantly changing the time horizon boundaries. The described method of changing the flow diagram consists either in changing all the flows at the same time or in a preemptive and smooth transition based on the introduction of a weighted flow diagram for various stationary modes, provided that their mismatch is minimized at neighboring time intervals corresponding to the intervals of constancy of consumption requests.