Optimization of co-production air separation unit based on MILP under multi-product deterministic demand

•The proxy model describes the production space of ASUs.;•Propose multi-product optimization scheduling under deterministic demand for co-production ASU;•Minimize oxygen emission based on avoiding frequent starting and stopping of ASU;•Verify the feasibility of the model by comparing a single produc...

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Veröffentlicht in:Applied energy 2022-11, Vol.325, p.119850, Article 119850
Hauptverfasser: Kong, Fulin, Liu, Yuxin, Tong, Lige, Guo, Wei, Qiu, Yinan, Wang, Li
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Sprache:eng
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Zusammenfassung:•The proxy model describes the production space of ASUs.;•Propose multi-product optimization scheduling under deterministic demand for co-production ASU;•Minimize oxygen emission based on avoiding frequent starting and stopping of ASU;•Verify the feasibility of the model by comparing a single product optimization. Optimizing gas distribution is one of the most important energy management issues in process industries such as metallurgy and the chemical industry. The air separation unit (ASU) is characterized by the simultaneous production of multiple products (oxygen, nitrogen, liquid oxygen, liquid nitrogen and liquid argon) and the mutual restriction of each product. The existing single-product scheduling models are not applicable to the actual process and the multi-product scheduling models are only for production processes and usually do not consider constraints such as ASU start/stop. Therefore, for the production as well as the transmission and storage processes of the co-production air separation system, the paper developed a MILP model, which uses a proxy model to express the production space of ASUs. This model minimizes oxygen emission based on avoiding frequent startup and shutdown of ASU, which uses the start-stop and load regulation of ASU, the start-stop of liquefier, and vaporizer as means, and considers device operating constraints. We verified the feasibility of the method by combining actual cases application and analyzing the result of the influence of single product optimization results on the balance of other products.
ISSN:0306-2619
1872-9118
DOI:10.1016/j.apenergy.2022.119850