Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System

Hybrid generating systems in power networks have emerged as a result of the rapid growth renewable infrastructure and widespread support for green energy. One most significant problems designing operating an electric generation system is efficient scheduling all facilities to meet rising demand. Economic load dispatch (ELD) generic procedure electrical system, ELD involves units reduce cost satisfy constraints. Metaheuristic algorithms are gaining popularity solving constrained issues because their larger global solution capacity, flexibility, derivative-free construction. In this research, problem integrated resources solved using unique model based on hybrid optimization. Furthermore, work considers multiobjectives such total wind cost, function thermal units, penalty function. The optimization optimizes plants within maximum minimum limitations. Additionally, turbines selected optimally by ensure demands. proposed combination particle swarm (PSO) cat (CSO), new algorithm referred oriented (POCSO). Finally, performance compared other conventional models. particular, POCSO 6.25%, 6%, 11.7%, 36%, 27%, 46.42% better than whale (WOA), elephant herd (EHO), moth-flame (MFO), dragonfly (DA), sealion (SLnO), CSO, PSO methods, respectively. Also, IEEE-30 bus best value 7.46%, 5.41%, 16.30%, 14.88%, 17.60%, 13.86%, 15.21%, 17.49%, 4.27% that PSO, SLnO, DA, MFO, EHO, WOA, multiagent glowworm (MAGSO), Harris hawks optimization-based feed-forward neural network (HHO-FNN)