Abstarct: Due to the maximum population growth, the increasing need for electricity in industry and domestic consumption, as well as the disadvantages of fossil fuels in electricity generation such as pollution, environmental degradation by the release of harmful gases and their extinction have led humans to turn to renewable energy. The Kalina cycle is a suitable technology and a useful process for converting low quality heat sources (low temperature and low pressure) into mechanical power and electricity. In this research, the solar Kalina cycle has been simulated and studied from the perspective of energy, exergy and exergo-economy; Then various factors such as temperature and inlet pressure to the turbine, the difference in the pinch point of the solar cycle evaporator are evaluated. The results show that the highest exergy efficiency occurs at the highest turbine inlet temperature of 433 K, which is about 8.9% for the proposed system and the maximum energy efficiency that can be achieved at the same temperature is 85 / 44%. Solar collectors, auxiliary boilers and storage tanks are the most important components from the exergo-economic point of view due to the high initial cost rate and exergy degradation. Analytical results indicate that the highest share of system exergy degradation is related to the solar field (linear parabolic collectors) and Kalina cycle has the lowest share in system exergy degradation, so new designs and investments should be made to improve collector performance and increase their efficiency. Necessary to be done. In economic terms, an increase in evaporator temperature and a pinch point difference leads to a decrease in the overall investment rate. Also, according to estimates, with the increase of turbine temperature from K393 to K435, the net output power has increased from 77 kW to 106 kW and the unit cost of power generation has decreased from $ / GJ 0.155 to $ / GJ 0.105, which is very economical. Is. Also, changing the solar flux improves the performance of the system from an exerco-economic point of view and increases energy efficiency and exergy. In the optimization of the NSGA-II algorithm, which is an effective method for multi-objective optimization, this algorithm is now recognized as one of the most efficient multi-objective evolutionary algorithms. One of the innovations of the present study has been the optimization of the three objectives of the system under study. Energy efficiency, exergy efficiency and unit cost of all products have been selected as the three objective functions for this optimization.