Thermodynamic analyses as well as optimisation studies based on maximum cooling coefficient of performance (COP) as thermal efficiency and optimum values of exergy efficiency and total input work of a three-stage compression transcritical CO2 cycle have been presented. A new triple-stage configuration of compression is presented, which uses two intercoolers to enhance the performance. For parametric optimisation, COP and total input work are selected as objective functions, which are calculated for different values of outlet pressure of first and second compressors. For optimisation, a procedure based on artificial neural network and particle swarm optimisation (PSO) algorithm is proposed. The procedure includes two stages. According to the parametric analysis data, in the first stage two different multilayer perceptron neural networks are trained. In the next stage, two distinct PSO algorithms are used to optimise total input work and thermal efficiency.
کلید واژگان :CO2 refrigerant; COP; coefficient of performance; exergy efficiency; Artificial neural network; particle swarm optimisation algorithm.
ارزش ریالی : 600000 ریال
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