A novel adaptive restarting genetic algorithm based congestion management

Abstract

This manuscript proposes a novel adaptive restarting genetic algorithm-based solution approach for rescheduling generation-based congestion control. The generator sensitivity values are considered to select generators to participate in the congestion management. The efficacy of the suggested technique is demonstrated on a 39-bus New England system and a modified IEEE 30 bus system, and a comparative study with other optimization strategies are established. The findings produced with the suggested technique for congestion management better the outcomes obtained with different methods. The presented approach ensures a superior convergence profile by eliminating local minima traps. This method also assists the independent system operator in managing congestion more efficiently.