A Soft Computing-Based Analysis of Congestion Management in Transmission Systems

Abstract

Congestion in the transmitting system is unitarily responsible for technological problems that appear, especially in a deregulated environment. The post-deregulation operation history of the electrical power system has placed greater pressure on the Independent System Operator (ISO) to assure a secure, congestion-less transmission network. Blackout and brownout voltage dip issues occur due to the heavy loading condition. Hence, this paper presents a novel approach for the relief of congestion by using a nature-inspired algorithm, namely Particle Swarm Optimization and Firefly Algorithm by considering various factors for re-dispatching active power of generators during overloading conditions. The algorithms are tested on IEEE 30 and IEEE 39 Bus standard test systems and the obtained results show the effectiveness of the proposed algorithm in the MATLAB environment. The congestion management (CoM) method is formulated as a constrained optimization problem with the objective function of relieving the overloading through minimization of factors such as Generator Shift Factor (GSF), Bus Sensitivity Factor (BSF), Line utilization Factor (LUF), and Congestion Index (CI). These factors are helpful to mitigate the transmission congestion, which in turn helps to reduce the real power losses.

Keywords

• congestion index
• deregulation
• independent system operator
• particle swarm optimization and firefly algorithm
• line utilization factor