Multi-objective optimization method for balancing complex petrochemical process productivity based on ANN modeling
A multi-objective optimization and balance technology, applied in the field of process simulation, can solve problems such as incomplete understanding of important attributes, complex industrial models of ethylene production, difficult multi-system multi-objective optimization, etc.
Active Publication Date: 2020-01-24
BEIJING UNIV OF CHEM TECH
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[0005] In view of the complex petrochemical industry, especially the ethylene production industrial model is too complex, the important attributes of the process cannot be fully understood and it is difficult to perform multi-system multi-objective optimization, etc., the present invention provides a complex model based on artificial neural networks (ANNs). Statistical modeling optimization method for petrochemical process
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Embodiment 1
[0078] ANNs models were established for the ethylene separation process for the ethylene plant and all the modeling data were derived from the rigorous model Aspen Plus (V8.4). Figure 5 A flow chart of the ethylene cryogenic separation system is given. On the basis of the ANNs model, the ethylene production and energy consumption were optimized by a hybrid algorithm with multiple objectives. Equations (10), (11) are the optimized objective functions:
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[0081] where MIN J 1 Indicates the minimum energy consumption, MAX J 2 Represents maximized ethylene production. C u and C W are the unit price of utilities and compressor shaft work, respectively. Table 1 gives the specific data.
[0082] Table 1. Utility Data and Unit Prices
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[0085] There are a total of 16 operating variables that need to be optimized, of which the compressor and heat exchanger positions are logical variables and the other 15 are continuous variables. ...
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The invention discloses a multi-objective optimization method for balancing the productivity of a complex petrochemical process based on ANN modeling. A MINLP model is established on the basis of an ANNs model, the MINLP model comprises a logic variable compressor position and a heat exchanger position, the optimal position is determined through a GA algorithm, then multi-target integration optimization is carried out at the optimal position through an NSGA-II algorithm, and a Pareto leading edge and a key decision variable leading edge are obtained. According to the method, the operation complexity of the petrochemical industry can be reduced to a great extent, and the method has important guiding significance for energy conservation and emission reduction of factories.
Description
technical field [0001] The invention belongs to the technical field of process simulation, and particularly relates to a multi-objective optimization method for balancing the production capacity of complex petrochemical processes based on ANN modeling. [0002] technical background [0003] In the petrochemical industry, the ethylene industry occupies a pivotal position, and about three-quarters of the petrochemical products are related to ethylene products. In 2018, China's ethylene production capacity was about 23.3 million tons per year, an increase of 9.6% compared with last year, accounting for 13.8% of global ethylene production. Energy consumption, however, accounts for more than 50% of the total cost, a 3.5% increase over last year. Therefore, balancing energy consumption and production efficiency in the petrochemical industry plays a crucial role in improving energy efficiency. [0004] At present, with the rapid development of computer level, modeling and simulati...
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IPC IPC(8): G06F30/20G06F111/06G06N3/02G06N3/08
CPCG06N3/02G06N3/086Y02P20/10
Inventor 王俊朱群雄贺彦林王钰叶玮
Owner BEIJING UNIV OF CHEM TECH