Optimal Power Flow (OPF) is allocating loads to plants for minimum cost while meeting the network constraints .It is formulated as an optimization problem of minimizing the total fuel cost of all committed plant while meeting the network constraints or power flow constraints. The variants of the problem are numerous which model the objective and the constraints in different ways. Optimal Power flow deals with minimizing generation cost while maintaining set of equality and equality constraints. 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. In this paper an attempt has been made to optimize each objective individually using Particle Swarm Optimization (PSO). In this method the system is initialized with a population of random solutions and searches for optima by updating generations. PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions called particles fly through the problem space by following the current optimum particles. The so developed algorithm for Optimization of each objective is tested on two systems i.e. on IEEE 26 and IEEE 30 bus system. Simulation results of IEEE 26 bus and IEEE 30 bus network are presented to show the effectiveness of the proposed method.