Energy, exergy, economic, and exergoeconomic analyses and optimization of a solar Kalina cycle using particle swarm optimization algorithm

Abstract

In the present research, a Kalina cycle has been analyzed from the energy, exergy, economic and exergoeconomic points of view. In this cycle, the water-ammonia solution is used as the working fluid. Firstly, the mass balance, energy, and exergy equations are solved, then the initial cost and exergy destruction cost have been calculated using the cost balance equations in different components. Finally, the optimization of solar Kalina's performance in terms of target functions, i.e., total cost rate and exergy efficiency, has been performed. To this end, a relationship between design parameters and target functions is derived using the neural network algorithm; then, the multiobjective optimization of the cycle is performed using the particle swarm optimization (PSO) algorithm. The results show that total work, net irreversibility, and total exergy efficiency in the base case are 296.2kW, 3671kW, and 0.0738, respectively. The exergoeconomic analysis indicates that the total cost rate was 366$h, and it was found that the solar collector and Kalina evaporator have respectively the maximum cost rate. The parametric analysis has been performed in terms of energy, exergy, and exergoeconomic to examine the effect of turbine's inlet temperature and pressure, and ammonia content on the cycle performance. The optimization results indicate that exergy efficiency and total cost rate are 0.08824, and 318.58$h, respectively. This represents an 19.5% increase in the exergy and a 12.95% reduction in cost rate compared to the base case.