Modelling and control of a hybrid renewable energy based hydrogen and electricity production and storage systems

Abstract This research investigated a hybrid renewable energy system that integrates solar and oceanic thermal energy to produce electricity and hydrogen through the utilization of a flat plate solar collector. The influence of these parameters on system performance and exergy degradation was analysed. A multi-objective optimization method based on a fast and elitist nondominated sorting genetic algorithm is applied to determine the best design parameters for the system. The findings of the multi-objective optimization indicated that the optimal rate of system exergy efficiency was 8.2%, while the system cost rate was determined to be $22.3/h. Sensitivity analysis demonstrated that enhancements in collector area, solar radiation intensity, and turbine inlet temperature exerted a beneficial influence on system performance.