Modeling and multi-objective optimization of a solar-boosted gas turbine cycle for green hydrogen production and potable water production

Global warming has caused lots of problems in recent years. Renewable energy can be a solution to this problem. In this research, a multigeneration system is modeled including a concentrated solar plan, Brayton cycle, Rankine cycle, organic Rankine cycle, absorption chiller, single-stage flash desalination, humidification, and dehumidification desalination, and PEM electrolyzer to produce power, cooling load, desalinated water, and hydrogen. The system is modeled in EES software. The results show that the system's overall energy and exergy efficiency is 46.6 % and 43.11 %, respectively. The total power production is 7533 kW after modeling the system in EES, by using a neural network, the data was transferred to MATLAB software. In MATLAB, multi-objective optimization was performed using the genetic algorithm to maximize exergy efficiency and minimize the cost rate. The optimized results show that the overall energy and exergy efficiencies are 46.1 % and 42.1 %, respectively. The total power production is 7628 kW.