Optimal Reactive Power Management Through a Hybrid BOA–GWO–PSO Algorithm for Alleviating Congestion

Abstract

In today's deregulated energy market, improving grid management in generating power with load optimization is a critical challenge. It is also perilous that the system does not have any problems owing to transmission line clogs. The Butterfly Optimization Algorithm is used for load balancing and load optimization in electricity markets. The proposed approach integrates Particle Swarm Optimization and Grey Wolf Optimizer, merging them with Butterfly Optimization Algorithm as a hybridised form to enhance exploration and exploitation skills. The benefit of the Butterfly Optimization Algorithm in general, as well as when it is employed to address difficult optimization issues, is validated using the New England 39 bus test system. The amalgamated algorithm approach was compared to other established meta-heuristic algorithms for the reactive power management under variable loading conditions. Using the realistic New England 39 bus system, the suggested algorithm minimizes transmission losses by 6.344% and operating costs by 6.347% with respect to the base case, respectively. The research work reveals that proposed amalgamated algorithm employing Butterfly Optimization Algorithm, Grey Wolf Optimizer, and Particle Swarm Optimization performs better and offers more potential in a range of situations. The proposed technique mathematical validation indicated that it has the capacity to tackle complex optimization issues and compete with contemporary peer-reviewed literature solutions.