Metaheuristic optimization approaches assess trade-offs between cost and reliability in hybrid renewable energy systems, indicating improved decision-making.
Key Points
MOPSO achieves the lowest cost of energy at 0.159 USD/kWh, with moderate reliability, showcasing optimization efficiency.
NSGA-II provides nearly perfect reliability at a cost of 0.179 USD/kWh, highlighting the trade-offs between cost and reliability.
The analysis reveals that NSGA-II offers a more diverse Pareto front, enhancing the design of hybrid renewable energy systems.
Both metaheuristic algorithms were implemented in Python with real-world load and resource profiles, illustrating practical application.