No abstract

No abstract

In this paper, exergy, exergoeconomic, and exergoenvironmental analysis of a gas turbine cycle and its optimization has been carried out by MOPSO algorithm. Three objective functions, namely, total cost rate, exergy efficiency of cycle, and CO 2 emission rate have been considered. The design variables considered are: compressor pressure ratio, combustion chamber inlet temperature, gas turbine inlet temperature, compressor, and gas turbine isentropic efficiency. The impact of change in gas turbine inlet temperature and compressor pressure ratio on CO 2 emission rate as well as impact of changes in gas turbine inlet temperature on exergy efficiency of the cycle has been investigated in different compressor pressure ratios. The results showed that with increase in compressor pressure ratio and gas turbine inlet temperature, CO 2 emission rate decreases, that is this reduction is carried out with a steeper slope at lower pressure compressor ratio and gas turbine inlet temperature. The results showed that exergy efficiency of the cycle increases with increase in gas turbine inlet temperature and compressor pressure ratio. The sensitivity analysis of fuel cost changes was performed on objective functions. The results showed that at higher exergy efficiencies total cost rate is greater, and sensitivity of fuel cost optimum solutions is greater than Pareto curve with lower total cost rate. Also, the results showed that sensitivity of changes in fuel cost rate per unit of energy on total cost rate is greater than the rate of CO 2 emission.

A comprehensive cost correlation analysis was conducted based on available cost correlations, and new equipment cost correlation models were proposed based on QUE$TOR modeling. Cost correlations for various types of equipment such as pumps, compressors, heat exchangers, air coolers, and pressure vessels were generated on the basis of extracted cost data. The models were derived on the basis of robust multivariable regression with the aim of minimizing the residuals by using the genetic algorithm. The proposed compressor models for both centrifugal and reciprocating types showed that the Turton cost estimation for carbon steel compressor and Matche’s and Mhhe’s data were compatible with the generated model. According to the results, the cost trend in the Turton correlation for carbon steel had a somewhat lower estimation than these correlations. Further, the cost trend of the Turton correlation for carbon steel pressure vessels was close to the presented model trend for both bullet and sphere types. The Turton cost trend for U-tube shell-and-tube heat exchangers with carbon steel shell and stainless steel tube was close to the proposed heat exchanger model. Furthermore, the Turton cost trend for the flat-plate heat exchanger using carbon steel was similar to the proposed model with a slight difference.

No abstract