Description and Examination of Optima Power Flow Using Traditional and Stochastic Optimization Techniques

Volume 6 Issue 2 May - July 2018

Research Paper

Description and Examination of Optima Power Flow Using Traditional and Stochastic Optimization Techniques

Ragaleela D.*, Sivanagaraju S.**

* Senior Assistant Professor, Department of Electrical and Electronics Engineering, PVPSIT, Vijayawada, Andhra Pradesh, India.

** Professor, Department of Electrical and Electronics Engineering, JNTUK, Kakinada, Andhra Pradesh, India.

Ragaleela, D and Sivanagaraju, S. (2018). Description and Examination Of Optima Power Flow Using Traditional and Stochastic Optimization Techniques. i-manager’s Journal on Power Systems Engineering, 6(2), 12-19. https://doi.org/10.26634/jps.6.2.14934

Abstract

In modern power systems, optima power flow plays a crucial role in optimizing different types of objective functions for progress and outlining. The purpose of Optima Power Flow (OPF) problem is to attain the optima solution of a considered test system objective function, like fuel cost and loss minimization by fine tuning the power system control variables. In this paper a new stochastic hybrid method, Particle Movement Bee Colony Algorithm (PMBCA) based on Particle Swarm Optimization (PSO) and Honey Bee Colony (HBC) is proposed in addition to existing methods. Comparisons of various traditional and heuristic optimization methods are considered to solve the OPF problems. The utility and efficacy of suggested algorithms is exemplarily tested on the IEEE 30-bus test system. Results prove that the PMBCA algorithm gives better solution and convergence characteristics to enhance the system performance compared with other methods.