OPTIMIZATION OF MICRO COMBINED HEAT AND POWER GAS TURBINE BY GENETIC ALGORITHM

In this paper, a comprehensive thermodynamic modeling and multi-objective optimization of a micro turbine cycle in combined heat and power generation, which provides 100KW of electric power. This CHP System is composed of air compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. In this paper, at the first stage, the each part of the micro turbine cycle is modeled using thermodynamic laws. Next, with using the energetic and exergetic concepts and applying economic and environmental functions, the multi-objectives optimization of micro turbine in combined heat and power generation is performed. The design parameters of this cycle are compressor pressure ratio (rAC), compressor isentropic efficiency (ηAC), GT isentropic efficiency (ηGT), CC inlet temperature (T3), and turbine inlet temperature (T4). In the multi-objective optimization three objective functions, including CHP exergy efficiency, total cost rate of the system products, and CO2 emission of the whole plant, are considered. Theexergoenvironmental objective function is minimized whereas power plant exergy efficiency is maximized usinga Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the result to the fuel cost is performed. The results show that at the lower exergetic efficiency, in which the weight of exergo-environmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergo-environmental objective. In addition, with increasing exergy efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases.

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