Modeling optimization method for purification process of high-sulfur natural gas based on detection of abnormal working conditions

Abstract

The invention discloses a method for modeling and optimizing the purification process of high-sulfur natural gas based on the detection of abnormal working conditions. Independent element analysis is used to extract independent elements, and the corresponding SPE statistics are calculated, and then compared with the set control limits to judge abnormal working conditions. The sample data collected under these conditions are discarded; the operating parameters of the purification process are used as the input variables of the extreme learning machine to establish a process model for the purification and desulfurization of high-sulfur natural gas. The output of the model is the content of H2S and CO2 in the purified gas. The particle swarm optimization algorithm optimizes the model structure of the extreme learning machine; the physical programming preference function designs different physical quantities of energy consumption and production under the same measurement criterion, and MOGA can realize the Pareto optimal solution set corresponding to the process operation parameters, energy consumption and production. The present invention utilizes the particle swarm optimized extreme learning machine to establish a statistical model for the purification and desulfurization process of high-sulfur natural gas, which improves the accuracy of the model; meanwhile, it also realizes multi-objective optimization of conflicting energy consumption and output.

Description

technical field [0001] The invention belongs to the intelligent energy-saving and production-increasing technology in the desulfurization production process of high-sulfur natural gas, and relates to a modeling optimization method for high-sulfur natural gas purification process based on detection of abnormal working conditions. Background technique [0002] The industrial process of high-sulfur natural gas is complex, and it is a typical chemical system with complex nonlinear dynamic characteristics. The purification and desulfurization process of high-sulfur natural gas mainly includes the following parts: the MDEA solution in the main absorption tower absorbs the acidic component H 2 S and CO 2 , hydrolysis reactor removal (COS), regeneration tower MDEA solution cycle regeneration and heat exchange process, the specific process flow process such as image 3 shown. How to establish an accurate and reliable industrial process model for purification and desulfurization of ...

AI Technical Summary

Problems solved by technology

However, output and energy consumption conflict with each other, and the optimization of one of the objectives must be at the expense of the other, and the units of each objective are often inconsistent, so it is difficult to objectively evaluate the pros and cons of the solutions to the two objective problems

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