Comparative Analysis of Particle Swarm Optimization With Classical Methods For Load Flow Analysis

Load flow studies are one of the basic  aspects of power system planning and operation. Objective of Load Flow Analysis is to provide the system parameters i.e: Complex Voltage, Complex Power P, and consequently currents, voltages in steady state. Load is a static quantity and it is the power that flows through transmission lines, due to which we prefer to call this Power Flow studies rather than load flow studies. Through the load flow studies we obtain the voltage magnitudes and angles at each bus in the steady state. Because the magnitudes of the bus voltages should be held within a specified limit. In addition to it we are using Particle Swarm Optimization Technique (PSO).Particle Swarm Optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. We are applying classical iterative methods Newton Raphson method, and Gauss- Siedel Method with artificial intelligence based algorithm Particle Swarm Optimization (PSO). So our objective is to build algorithm to get optimization of results. For reference we will compare PSO with Gauss- Siedel and Newton-Raphson and also implemented their codes in Matlab Programming