A Quasi-Oppositional Heap-Based Optimization Technique for Power Flow Analysis by Considering Large Scale Photovoltaic Generator

Load flow analysis is an essential tool for the reliable planning and operation of interconnected power systems. The constant increase in demand, apart from increased intermittency generation due to renewable energy sources without proportionate augmentation transmission system infrastructure, has driven systems function nearer their limits. Though (PF) solution may exist such circumstances, traditional Newton–Raphson based PF techniques fail computational difficulties owing singularity Jacobian Matrix during critical conditions faces solving ill-conditioned To address these problems assess impact large-scale photovoltaic generator (PVG) integration on studies, a derivative-free quasi-oppositional heap-based optimization (HBO) (QOHBO) technique proposed present paper. In approach, concept learning applied HBO enhance convergence speed. efficacy effectiveness QOHBO-PF are verified by applying it standard IEEE robustness algorithm validated under maximum loadability limits high R/X ratios, comparing results with other well-known methods suggested literature. thus obtained show that less computation time, further enhancement reliability presence PVG, ability provide multiple solutions can be utilized voltage stability analysis.