Comparative Analysis of Non-Bio Inspired Optimization Techniques with Renewable Energy Sources

Renewable energy, particularly photovoltaic (PV) solar energy, is emerging as a cleaner, low-impact alternative to traditional power sources, critical for reducing carbon emissions amid rising global demand. Solar energy offers a reliable, sustainable boost to energy systems while maintaining cost efficiency. To optimize solar PV management, diverse, non-bio inspired optimization methods-Linear Programming (LP), Quadratic Programming (QP), Integer Programming (IP), Dynamic Programming (DP), and Sequential Quadratic Programming (SQP) were employed. These approaches enable precise parameter tuning, yielding optimized solutions that enhance efficiency and sustainability. By systematically applying these techniques, effective PV management that supports a greener, more resilient energy landscape is achieved.