标题：An architectural approach to process control of gas compressor stations with a low temperature separation gas preparation unit based on a digital twin
摘要：This article lists a part of a study of possibilities of using and integrating digital twins of the existing high-tech enterprise processes on the examples of a high-pressure gas compressor station and a gas treatment plant using low-temperature separation of an oil and gas enterprise using an architectural approach. The need for the use of digital twins (DT) in the high-tech industry is due to the inability to effectively conduct full-scale tests to select the necessary operating modes in the implementation framework of technological processes with varying parameters (high cost and increased resource consumption compared to the creation of a DT). The main difference between DT and conventional models is the three-dimensional matrix of input variable parameters that can be given to DT for processing in order to obtain the most correct output data when performing simulations. At the same time, millions of operational cycles can be generated in real time, which allows us to most effectively solve various business problems. For example, the task of finding optimal solutions and prototype configurations under study.
其他摘要：This article lists a part of a study of possibilities of using and integrating digital twins of the existing high-tech enterprise processes on the examples of a high-pressure gas compressor station and a gas treatment plant using low-temperature separation of an oil and gas enterprise using an architectural approach. The need for the use of digital twins (DT) in the high-tech industry is due to the inability to effectively conduct full-scale tests to select the necessary operating modes in the implementation framework of technological processes with varying parameters (high cost and increased resource consumption compared to the creation of a DT). The main difference between DT and conventional models is the three-dimensional matrix of input variable parameters that can be given to DT for processing in order to obtain the most correct output data when performing simulations. At the same time, millions of operational cycles can be generated in real time, which allows us to most effectively solve various business problems. For example, the task of finding optimal solutions and prototype configurations under study.
