A Multi-objective Hybrid Optimization for renewable energy integrated Electrical Power Transmission Expansion Planning

Due to the large size of conventional electrical power transmission systems and number uncertainties involved, achieving most favourable Transmission Expansion Planning solution turns out be almost impossible. The proposed method intends develop a novel solve problems in electric incorporating renewable energy sources like wind turbines Photo Voltaic array using IEEE 24 Reliability Test System. For enhancing efficiency search processes make its use easier on diverse networks operations, hybridization two renowned meta-heuristic algorithms known as Grey Wolf Optimization (GWO) Genetic Algorithm (GA) termed with (GWGA) is adopted. A distance factor based best position current wolf optimization introduced for technique gives quick promising reduced computational time. GWO GA are combined suitably achieve advantages both algorithms. With this model, investment cost line maximum amount that can distributed consumer optimized an objective minimum load shedding. Among state-of-the-art techniques considered, remarkable performance percentage improvement expansion plan terms reduction shedding minimization has been obtained GWO, but when hybridized GA, 13.42% function 18.65% achieved population 60. Hence, guarantees generate faster convergence resulting