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Problems and methods of improving dispatcher decision-support systems for gas trunk pipelines

DOI 10.18127/j19997493-201804-03


D.A. Tsepelev – Master, Assistant, Department , Vladimir State University named after A.&N. Stoletovs

The Russian gas trunk pipeline has no analogs in the world in terms of it's length – there are 154 thousand kilometers of trunk pipelines used for transporting gas to either internal users in Russia, or foreign users all over the CIS and Western Europe. According to the forecasts, gas delivery volumes will have been increased up to 670 billion cubic meters by 2020. However, at the present moment there are more than 21% of trunk pipelines older than 33 years (which is standard service time), which can lead to emergency situations, especially in the zones with geodynamic activity, areas with stressed bowels, regions with faults and active emanations of aggressive gases. Magnetic, electric and warmth anomalies, along with gas transportation preparation have a big influence in corrosion and destruction of pipes.
In cases of the emergency situations a dispatcher has to detect it, find out its type and take actions in order to localize it and eliminate the consequences, i.e. move systems from the emergency mode to the standard one. There are 3 types of possible emergency situations:
unauthorized valving movement (turn on/off) – an emergency situation caused by turning off the main crane on the pipeline or turning on the crane between two papes with the pressure difference;
wrong sensor data – an emergency situation caused by sensor fault;
a gas leak caused by partual of full pipe break on the linear part of the gas trunk pipeline.
In case of emergency situation gas trunk pipeline dispatcher has to fix it quickly. Errors can happen during the issue liquidation because of phychologic pressure, hard time limitations, suddenness factor and big information overhead. Since the emergency situations on gas trunk pipeline happen rarely, but their effects can be disastrous, there is a need in teaching dispatchers to detect emergency situations and to take immediate and adequate actions in order to localize them. The solution for the defined task can be reached via constant training of dispatchers using the real-time emulators of hardware-software complexes used in dispatching stations. The idea of dispatcher education can be extended with increasing of education quality using automated data analysis.
Using the user-defined value of time period Δt telemetry system is requested for sensor data, which is analyzed by the intellectual system. If each sensor value fits the predefined bounds then it means that the system is working in the standard state. However, if at least one of the sensors has a value out of normal bounds then the analysis module should be executed. A single sensor value different from a normal one, cannot provide enough confidence in the emergency situation, that's why more precise results can be gathered during the next intervals Δt in case of a real emergency situation.
Before handling the pipeline break program should know the stage of the emergency situation, i.e. was it localized or not. If localization has not been executed yet, then a set of actions should be taken to support the dispatcher in making a decision about localizing an area of the gas trunk pipeline. The localization principle is very straightforward: all the pipelines directed to the expected place of the break should be closed, but the square of the part turned off from the gas transportation system, should be minimal. In other words, localization means building so-called «circles» around the emergency area. If the chosen area with a minimal «circle» cannot manage the handling of the emergency situation for any reason then the «circle» should become wider etc. As a result, the broken pipeline gets several-kilometer range of a pipe, which was cut. In order to do this, first of all a place in a pipeline break should be detected.
In order to improve the quality of the dispatcher decision support system it's possible to improve the quality of the collected data. First of all, monitoring data should be collected not in one mode, but in two – standard mode, when the data is requested from all the sensors, and emergency mode, when only important data about the part of the pipe where the leak had happened is collected. Secondly, it might be possible to predict values of the sensors system that have not been requested for a long time based on the previous values, assuming that there is no emergency situation in that part of the pipe. Thirdly, it is possible to change the order of the registers to reduce the amount of data transfered with each request. It can help to increase the speed of data gathering. And finally, it might be possible and useful to change the order of the requests to the sensors.

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