Daily Operation Optimization of a Residential Molten Carbonate Fuel Cell Power System Using Genetic Algorithm

摘要

To decrease the cost of electricity generation of a residential molten carbonate fuel cell (MCFC_power system,multi-crossover genetic algorithm (MCGA),which is based on "multi-crossover"and "usefulness-based selection rule",is presented to minimize the daily fuel consumption of an experimental 10kW MCFC power system for residential application.Under the operating conditions obtained by MCGA,the operation constraints are satisfied and fuel consumption is minimized.Simulation and experimental results indicate that MCGA is efficient for the operation optimization of MCFC power systems.