1Associate Professor, Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu, India
2UG Student, Department of EEE, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu, India
3Assistant Professor, Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamilnadu, India
4Assistant Professor, Department of Electrical and Electronics Engineering, Government College of Engineering, Chengipatti
Online published on 1 November, 2018.
Optimal power flow could be a mathematical model that represents a physical power grid optimization drawback. It is a challenging task developed as an extremely strained non-linear program whose resolution states the best in operation condition of the system. This operation purpose should satisfy the full power demand and limit constraints whereas minimizing a value operate. This paper presents a changed Flower impregnation algorithmic rule (MFPA) to point out the benefits of projected algorithmic rule a comparative study with alternative meta-heuristic optimization techniques is applied. The numerical results clearly show that the improved algorithm provides higher results than Cuckoo-search and customary flower impregnation (FPA) algorithms in terms of fuel value worth and time needed to achieve international best resolution. In order for instance the effectiveness of the projected algorithmic rule, it has been checked on a changed IEEE 30-bus test system.
Flower impregnation algorithmic rule (MFPA), meta-heuristic, cuckoo-search. Customer flower
