Thermal/econmic/environmental considerations in a multi-geneation layout with a heat recovery process; A multi-attitude optimization based on ANN approach

The proposed system is designed to address the growing demand for sustainable and efficient energy solutions that can minimize greenhouse gas emissions while meeting the increasing energy needs of a modern world. The integrated approach of the system allows it to produce not only electricity but also hydrogen and fresh water from seawater, making it a comprehensive solution to multiple challenges. The system comprises several components that work together including a gas turbine unit, Rankine and organic Rankine cycles, a multi-effect desalination (MED) system, and a proton exchange membrane (PEM) electrolyzer. One significant characteristic of this system is its ability to generate hydrogen, which is later combined with the inlet fuel of the gas turbine. This novel methodology presents a more environmentally friendly fuel alternative, showcasing its potential to enhance combustion efficiency in a sustainable manner. To ensure the viability and feasibility of the system, a MATLAB function was utilized for calculating the base case scenario, followed by a GA optimization technique with the aid of a machine learning model to minimize run-time. In the given scenario, the total cost rate is measured at 3726 $/h, with an exergy efficiency of 54% and a normalized CO2 emission of 305 kg/GJ. Following the optimization process, significant enhancements can be observed. The cost rate decreases by 2202 $/h, the exergy efficiency improves from 54% to 55.61%, and the annual CO2 emissions decrease from 133,760 metric tons to 50,320 metric tons. Moreover, the implementation of blended fuel leads to a 10% decrease in normalized CO2 emissions.