Profitability enhancement of a hybrid system including thermal-wind-CAES-fuel cell with incorporation of imbalance cost

In deregulated energy markets, the incorporation of renewable resources stances substantial economic and operational challenges. This paper considers a hybrid system configuration with wind farms, compressed air energy storage, and hydrogen fuel cells for enhancing system profitability and reducing imbalance costs due to prediction errors. An innovative imbalance cost model is presented on the basis of projected and real wind speed statistics for four diverse sites across India. The system is verified on modified IEEE 30, 57, and 118-bus systems for a scalability and stability study under different grid complexities. Optimization is performed based on sequential quadratic programming, artificial bee colony, and the artificial gorilla troops optimizer algorithms. Outcomes indicate that the addition of compressed air energy storage and hydrogen fuel cells resulted in mean profit enhancements of as much as 5.3% (30-bus), 6.2% (57-bus), and 6.7% (118-bus), respectively, over wind-only setups. The artificial gorilla troops optimizer algorithm performed superior compared to others in optimizing economic payback and reducing system risk, as evaluated by value at risk and conditional value at risk indicators. These results emphasize the feasibility and efficacy of the suggested hybrid model for maximizing profitability and operational robustness in competitive electricity markets.