A Review On Improved Partical Swarm Optimization For Multi-Ojective Optical Power Flow Considering The Cost,Loss, Emission And Voltage Stability Index

Abstract

Traditional Economic Load Dispatch deals with minimizing generation cost while maintaining set of equality and equality constraints. On the other hand, the fossil fuel plants pollutes environment by emitting some toxic gases. Thus conventional minimum cost operation can not be the only basis for generation dispatch; emission minimization must also be taken care of. Power system must be operated in such a way that both real and reactive powers are optimized simultaneously.  Reactive powers should be optimized to provide better voltage profile as well as to reduce system losses. Thus the objective of reactive power optimization problem can be seen as minimization of real power loss over the transmission lines. Now a days large integrated power systems are being operated under heavily stressed conditions which imposes threat to voltage stability. Voltage collapse occurs when a very low voltage profile or collapses. All these four objectives are to be met for efficient operation and control. The results of all the four objectives are conflicting and noncommensurable. Hence an efficient control which meets all the specified objectives is required.

            In this project an attempt has been made to optimize each objective individually using Particle Swarm Optimization. The so developed algorithm for Optimization of each objective is tested on two systems i.e. on  IEEE 30 and IEEE 57 bus system. In this work a method has been proposed to solve multiobjective optimization method using fuzzy decision satisfaction method while the objectives are minimized individually using Particle Swarm Optimization. Simulation results of IEEE 30 bus and IEEE 57 bus network are presented to show the effectiveness of the proposed method.