PSOα: A Fragmented Swarm Optimisation for Improved Load Frequency Control of a Hybrid Power System Using FOPID

Particle swarm optimisation (PSO) is one of the widely adopted meta-heuristic methods for solving real-life problems. Its practical utility can be further enhanced by improving its performance. In order to acheive this, academics have presented several variants original PSO over past few years, including quantum (QPSO), bare-bones (BB-PSO), hybrid PSO, fuzzy etc. this paper, performance improved proposing a fragmented approach known as PSOα. The PSOα tested and compared with PSOs 14 different benchmarking cost functions validate efficacy. analysis also carried out see impact α on It observed that average value function 50 simulations obtained using lower than standard in 12 benchmark functions. Similarly, outperforms 13 when best fitness achieved simulations. Finally, proposed applied solve well-known problem load frequency control (LFC) power systems. A test system comprising both renewable traditional sources considered evaluate efficacy technique. fractional proportional-integral-differential (FOPID) controller used, whose parameters are optimised achieving LFC. fragmentation other techniques improve their