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 are presented, which provides 100 kW of electric power. This combined heat and power system is composed of air compressor, combustion chamber, air preheater, gas turbine, and a heat recovery heat exchanger. 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, gas turbine isentropic efficiency, com-bustion chamber inlet temperature, and turbine inlet temperature. In the multi-objective optimization three objective functions, including the combined heat and power exergy efficiency, total cost rate of the system products, and CO₂ emission of the whole plant, are considered. The exergo-environmental 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. [ABSTRACT FROM AUTHOR]