Title of article
Thermodynamic and exergoenvironmental analyses, and multi-objective optimization of a gas turbine power plant
Author/Authors
Pouria Ahmadi، نويسنده , , Ibrahim Dincer، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
12
From page
2529
To page
2540
Abstract
The present study deals with a comprehensive thermodynamic and exergoeconomic modeling of a Gas Turbine (GT) power plant. In order to validate the thermodynamic model, the results are compared with one of the largest gas turbine power plants in Iran (known as Shahid Salimi Gas Turbine power plant). Moreover, a multi-objective optimization is performed to find the best design variables. The design parameters considered here are air compressor pressure ratio (rAC), compressor isentropic efficiency (ηAC), gas turbine isentropic efficiency (ηGT), combustion chamber inlet temperature (T3) and gas turbine inlet temperature (TIT). In the multi-objective optimization approach, certain exergetic, economic and environmental parameters are considered through two objective functions, including the gas turbine exergy efficiency, total cost rate of the system production including cost rate of environmental impact. In addition, fast and effective non-dominated sorting genetic algorithm (NSGA-II) is applied for the optimization purpose. The thermoenviroeconomic objective function is minimized while power plant exergy efficiency is maximized using a power full developed genetic algorithm. The results of optimal designs are obtained as a set of multiple optimum solutions, called ‘the Pareto optimal solutions’. Moreover, the optimized results are compared with the working data from the case study. These show that by selecting the optimized data 50.50% reduction in environmental impacts is obtained. Finally, sensitivity analysis of change in objective functions, when the optimum design parameters vary, is performed and the degree of each parameter on conflicting objective functions has been determined.
Keywords
Energy , Exergy , Efficiency , Exergoeconomics , Genetic Algorithm , Sustainability , Environmental impact , Optimization
Journal title
Applied Thermal Engineering
Serial Year
2011
Journal title
Applied Thermal Engineering
Record number
1045658
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