PRODUCTION PLANNING OF OIL-REFINERY UNITS FOR THE FUTURE FUEL MARKET IN BRAZIL

PRODUCTION PLANNING OF OIL-REFINERY UNITS FOR THE FUTURE FUEL MARKET IN BRAZIL

MENEZES, B. C.; MORO, L. F. L.; GROSSMANN, I. E.; KELLY, J. D.; MEDRONHO, R. A.; PESSOA, F. P.

Artigo:

The oil industry in Brazil has accounted for US$ 300 billion in investments over the last 10 years and further expansions are planned in order to supply the needs of the future fuel market in terms of both quantity and quality. This work analyzes the Brazilian fuel production and market scenarios considering the country’s planned investments to prevent fuel deficit of around 30% in 2020. A nonlinear (NLP) operational planning model and a mixed-integer nonlinear (MINLP) investment planning model are proposed to predict the national overall capacity for different oil-refinery units aggregated in one hypothetical large refinery considering four possible future market scenarios. For the multi-refinery case, a phenomenological decomposition heuristic (PDH) method solves separated the quantity and logic variables in a mixed-integer linear (MILP) model, and the quantity and quality variables in an NLP model. Iteratively, the NLP model is restricted by the MILP results.

The oil industry in Brazil has accounted for US$ 300 billion in investments over the last 10 years and further expansions are planned in order to supply the needs of the future fuel market in terms of both quantity and quality. This work analyzes the Brazilian fuel production and market scenarios considering the country’s planned investments to prevent fuel deficit of around 30% in 2020. A nonlinear (NLP) operational planning model and a mixed-integer nonlinear (MINLP) investment planning model are proposed to predict the national overall capacity for different oil-refinery units aggregated in one hypothetical large refinery considering four possible future market scenarios. For the multi-refinery case, a phenomenological decomposition heuristic (PDH) method solves separated the quantity and logic variables in a mixed-integer linear (MILP) model, and the quantity and quality variables in an NLP model. Iteratively, the NLP model is restricted by the MILP results.

Palavras-chave:

DOI: 10.5151/chemeng-cobeq2014-1838-17267-161843

Referências bibliográficas

• [1] MENEZES, B. C.; MORO, L. F. L.; LIN, W. O.; MEDRONHO, R. A.; PESSOA, F. P. Nonlinear Production Planning of Oil-Refinery Units for the Future Fuel Market in Brazil: Process Design Scenario-Based Model. Ind. Eng. Chem. Res., v. 52, p. 4352-4365, 2014.
• [2] PERRISÉ, J. B. Oil-Refining Evolution in Brazil. M.D. Thesis, State University of Rio de Janeiro, August 2007.
• [3] PETROBRAS. Business Plan 2013–2017. Rio de Janeiro, March 2013.
• [4] SAHINIDIS, N. V.; GROSSMANN, I. E.; FORNARI, R. E.; CHATHRATHI, M. Optimization Model for Long Range Planning in the Chemical Industry. Comput. Chem. Eng.,v. 13(9), p. 1049-1063, 1989.

Como citar:

MENEZES, B. C.; MORO, L. F. L.; GROSSMANN, I. E.; KELLY, J. D.; MEDRONHO, R. A.; PESSOA, F. P.; "PRODUCTION PLANNING OF OIL-REFINERY UNITS FOR THE FUTURE FUEL MARKET IN BRAZIL", p-12856-12863. In: Anais do XX Congresso Brasileiro de Engenharia Química - COBEQ 2014 [= Blucher Chemical Engineering Proceedings, v.1, n.2]. São Paulo: Blucher, 2015.
ISSN 23591757, DOI 10.5151/chemeng-cobeq2014-1838-17267-161843