Optimal Power Flow Using Hybrid Particle Swarm Optimization And Moth Flame Optimizer Approach

Résumé: In this study, the most common problem of the current power system named optimal power flow (OPF) is optimized using the recently hybrid meta-heuristic optimization technique Particle Swarm Optimization-Moth Flame Optimizer (PSO-MFO) algorithm. Hybrid PSO-MFO is an incorporation of PSO used for exploitation stage and MFO for exploration stage in an uncertain environment. The position and velocity of the particle are restructured according to Moth and flame location in each iteration. The hybrid PSO-MFO technique is carried out to solve the OPF problem. The performance of this technique is deliberated and evaluated on the standard IEEE 30-bus test system. The problems considered in the OPF are fuel cost reduction and Active power loss minimization. The results obtained with hybrid PSO-MFO technique is compared with original PSO and MFO.

Publié dans la revue: Revue des sciences et sciences de l’ingénieur