Optimization of a modified double-turbine Kalina cycle by using Artificial Bee Colony algorithm

Owing to appropriate performance of ammonia-water as a working fluid over two-phase region when exploiting low-temperature heat sources, a modified low-temperature double-turbine Kalina cycle system is designed to boost thermal efficiency. Due to low pressure after the second turbine, it is not affordable to use more than two turbines. Input mass flow rate of the second turbine is supplied by adding heat to the output liquid ammonia-water mixture from the first separator, separating the vapor at the outlet of the first turbine before blending the two streams. In order to reach the optimum thermal efficiency of the cycle, ABC (Artificial Bee Colony) algorithm is implemented as a novel powerful multi-variable optimization algorithm. Considering the structure of the algorithm, convergence speed and accuracy of solutions have been considerably enhanced when compared to those of GA, PSO and DE algorithms. Such a relative enhancement is indicated by limit parameter and reducing probability of occurrence of local optimum problem. In this paper, thermal efficiency is selected as the objective function of ABC algorithm where its optimum value for the suggested Kalina cycle is found to be 26.32%. Finally, effects of the first separator inlet pressure and temperature, basic ammonia mass fraction and mass flow rate of the ammonia-water working fluid on net power output, required heat energy for the cycle and thermal efficiency are investigated.