Optimization procedure to minimize FPSO fuel consumption under two operation modes in a Brazilian deep-water oil field
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Data
2018-01-01
Autores
Allahyarzadeh-Bidgoli, Ali
Dezan, Daniel Jonas
Salviano, Leandro Oliveira
de Oliveira, Silvio
Yanagihara, Jurandir Itizo
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Resumo
A Floating, Production Storage and Offloading (FPSO) plant is a high energy consumer (from a few to several hundreds of megawatts). Thus, a fuel consumption optimization procedure can be applied to find optimum operating conditions of the unit, saving money and CO2 emissions from oil and gas processing companies. In this work, two different operating conditions of the Brazilian deep water oil field in pre-salt areas are investigated for FPSO fuel consumption minimization: (1) 50% BS&W oil content and; (2) high water and CO2 in oil content. The impact of eight thermodynamic input parameters on fuel consumption of the FPSO unit is investigated by the Smoothing Spline ANOVA (SS-ANOVA) method. From SS-ANOVA, the input parameters that presented the highest impact on fuel consumption were selected for analysis in an optimization procedure. The numerical simulations of the whole FPSO unit are performed by using Aspen HYSYS®. The optimization procedure uses a modified Genetic Algorithm, which is a combination of Genetic Algorithm and SQP method. The results from the optimized case indicated that the minimization of fuel consumption is achieved by increasing the operating pressure in the third stage of the separation train and by decreasing the operating temperature in the second stage of the separation train for both operation modes. There was a reduction in power demand of 10.08 % for mode 1 and 2.92 % for mode 2, in comparison to the baseline case. Consequently, the fuel consumption of the plant was decreased by 8.34% for mode 1 and 2.43% for mode 2, when compared to the baseline case.
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Deep-water oil field, FPSO, Fuel consumption optimization, Genetic algorithm, SQP method, Thermodynamic analysis
Como citar
ECOS 2018 - Proceedings of the 31st International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems.