Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages

Abstract

Due to the harmful effects and depletion of non-renewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively.