Thermodynamic analysis and optimization of a geothermal Kalina cycle system using Artificial Bee Colony algorithm

Highlights

A geothermal Kalina cycle system for providing electrical load is selected.

Energy and exergy analysis of the Kalina cycle are performed.

Artificial Bee Colony algorithm is conducted for the optimization.

Thermal and Exergy efficiencies are selected as the objective functions.

Effects of important parameters on the performance of the cycle are investigated.

Abstract

In this paper, thermodynamic analysis is carried out for a geothermal Kalina cycle employed in Husavic power plant. Afterwards, the optimum operating conditions in which the cycle is at its best performance are calculated. In order to reach the optimum thermal and exergy efficiencies of the cycle, Artificial Bee Colony (ABC) algorithm, a new powerful multi-objective and multi-modal optimization algorithm, is conducted. Regarding the mechanism of ABC algorithm, convergence speed and precision of solutions have been remarkably improved when compared to those of GA, PSO and DE algorithms. Such a relative improvement is indicated by a limit parameter and declining probability of premature convergence. In this research, exergy efficiency including chemical and physical exergies and thermal efficiency are chosen as the objective functions of ABC algorithm where optimum values of the efficiencies for the Kalina cycle are found to be 48.18 and 20.36%, respectively, while the empirical thermal efficiency of the cycle is about 14%. At the optimum thermal and exergy efficiencies, total exergy destruction rates are respectively 4.17 and 3.48 MW. Finally, effects of the separator inlet pressure, temperature, basic ammonia mass fraction and mass flow rate on the first and second law efficiencies are investigated.

Keywords

  • Geothermal Kalina cycle;
  • Artificial Bee Colony algorithm;
  • Thermodynamic optimization;
  • Thermal efficiency;
  • Exergy efficiency

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