Hybrid COA-IWGAN approach using thermal-solar integrated system with minimised carbon footprint

This paper proposes a hybrid technique for a thermal-solar system. The proposed technique combines the cheetah optimisation algorithm (COA) and the improved Wasserstein generative adversarial network (IWGAN), commonly named COA-IWGAN. The aim is to decrease carbon emissions of the system. The COA generates the control signal of the voltage source converter (VSC), and IWGAN predicts the optimal control signal of the converter. The COA-IWGAN approach was performed MATLAB platform. From the result, the proposed method loss of carbon emission (LCE) is 54 CO(2)KWh at 4% of loss of power supply probability (LPSP), cost is $0.522/kWh and exergy efficiency is 27%. The result shows proposed approach demonstrates significant improvements compared to existing methods.