Energy optimization for liquefaction process of natural gas in peak shaving plant
M. Mokarizadeh Haghighi Shirazi and
Energy, 2010, vol. 35, issue 7, 2878-2885
One of the most important sections in the gas peak shaving plant regarding the energy consumption is the liquefaction process of natural gas (NG). Thus, selection and development of this process with the lowest energy consumption, offer huge potential energy and cost benefits. Here, a single-stage mixed refrigerant (SMR) cryogenic cycle with two compression stages has been selected for producing Liquefied Natural Gas (LNG). Energy consumption of the process as an objective function is optimized by describing key variables of the design. The proposed process’s calculations of thermodynamic concepts and properties are applied in MATLAB software to generate the objective function; furthermore Genetic Algorithm (GA) is used as an optimization method. Concerning works done in this area, more key parameters – related directly to the objective function – are introduced in this paper. A low irreversibility is due to enhanced values of key parameters in the LNG heat exchanger observed under a low temperature difference between hot and cold composite curves. Finally, the exergy lost of equipments in the proposed process are evaluated and analyzed in details.
Keywords: Gas peak shaving; Exergy analysis; Mixed refrigerant cryogenic cycles; Liquefied natural gas; Energy optimization; Genetic Algorithm (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (9) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:35:y:2010:i:7:p:2878-2885
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Series data maintained by Dana Niculescu ().