Systematic analysis and multi-objective optimization of integrated power generation cycle for a thermal power plant using Genetic algorithm

Abstract

This study presents systematic analysis and optimization of an integrated system consisting of internal reforming solid oxide fuel cell (SOFC) and gas turbine (GT) as a topping system that feeds the waste heat to a bottoming system consists of a steam cycle (ST) and organic Rankine cycle (ORC) with HFE7000 as working fluid. The study includes energy, exergy, exergo-economic, and environmental analysis. We investigate the possibility of adding SOFC to the existing GT-ST combined powerplant and evaluates the improvement in exergy efficiency and levelized cost of electricity. Also, we propose a novel setup to eliminate the necessity of the water pump and auxiliary steam generator for SOFC’s fuel reforming process. The system uses the Stirling engine to heat supplied liquid natural gas (LNG) fuel to a usable temperature condition; Using the Stirling engine increases the system’s overall efficiency by eliminating the need for the fuel compressor and suppression valve. A mathematical model of the system is developed to evaluate system conditions in Engineering Equation Solver (EES) program and a multi-objective Non-dominated Sorting GeneticAlgorithm (NSGA-II) is used in MATLAB to promote the best operating condition in which minimal levelized cost of electricity is achieved while maximizing exergy efficiency is considered. The results show that energetic and exergetic efficiencies reach the value of 72.66% and 69.23%, respectively. The cost of electricity is calculated as 14.46 [cent kWh-1], of which 1.33 [cent kWh-1] is related to environmental taxes due to air pollution and greenhouse gas emissions. This study can be used as a road map to how existing gas-steam hybrid cycle powerplants can be improved by adding additional equipment without the need to replace currently installed equipment.