Adaptive Particle Swarm Optimization Using Velocity Feedback for Optimal Congestion Management

This paper present, a new Velocity Feedback Adaptive Particle Swarm Optimization (VFAPSO) algorithm for Congestion Management (CM) using optimal re-scheduling of both real and reactive power generation with capacitor reactive support. The optimal rescheduling of powers in a pool model is formulated as a constrained nonlinear optimization problem. The paper proposes the application of VFAPSO algorithm to solve the constrained nonlinear optimization problem. In the proposed method the inertia weight is dynamically adjusted using the information of average velocity of swarm as feedback. The proposed method deals with an adaptive strategy for tuning the parameters of Particle Swarm Optimization method based on the analysis of the dynamics of PSO. The effectiveness of the proposed method has been tested on 39-bus New England Test system. The simulation experiments reveal that the proposed method performs better than conventional PSO.