Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 7, Pages: 1-12
Mohammad Amin Javadi1* and Hossein Ghomashi2
1Department of Mechanical Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran; [email protected] 2School of Mechanical Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran; [email protected]
*Author for Correspondence
Mohammad Amin Javadi
Department of Mechanical Engineering, West Tehran Branch, Islamic Azad University, Tehran, Iran; [email protected]
Background/Objectives: The welfare and comfort of people in the world is directly related to consuming energy and its economic supply, which depends on quantity of energy resources. This has been turned into an important challenge with respect to rapid growth at level of request for energy in the world. Methods/Statistical analysis: In this multiobjective optimization that has been carried out by Non-Dominated Sorting Genetic Algorithm (NSGA-II), two objective functions of exergy efficiency and produced power costs composing of the cost of injected fuel into combustion chamber and duct burner as well as exergy loss cost and investment cost have been studied. Findings: The efficiency of Abadan combined cycle power plant depends on design parameters including gas turbine input temperature, compressor pressure ratio, and pinch point temperature and any change occurring in these parameters may lead to noticeable change in objective functions, so that the efficiency of this power plant is increased after optimization up to 7.12 % and heat rate is correspondingly reduced from 7503 (kJ/kWh) to 7149 (kJ/kWh). Similarly, exergy destruction in total system shows 8.37 reduction. Applications/Improvements: In this research Abadan combined cycle power plant has been perfectly modeled in terms of thermodynamics and the given results were compared with output data from Thermo-Flow Software in order to ensure the validity of the modeling code.
Keywords: Abadan Combined Cycle Power Plant, Exergy Efficiency, Exergy Destruction, Optimization, NSGA-II
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