A New Effective Hybrid Meta-heuristic Algorithm for Solving AC Transmission Expansion Planning Problem

AC model is known as the most accurate model for transmission expansion planning (TEP) problem.However, finding an optimal solution is still a difficult task due to the complex, non-linear, and non-convex nature of the ACTEP.In this study, a new hybridization of Differential Evolution (DE) and Zebra Optimization Algorithm (ZOA) algorithms, called DE-ZOA, is proposed to solve the ACTEP problem.The main idea of the hybrid algorithm is to improve the exploitation strategy of the DE algorithm based on the best individual in the population, which is inspired by the ZOA algorithm.The results given by the proposed DE-ZOA algorithm are compared to the original DE, ZOA, and other existing algorithms in both Graver 6 bus and IEEE 24 bus systems.The results show that the total cost obtained by the proposed DE-ZOA algorithm is smaller than 44.33% and 0.66% compared to the ZOA and DE algorithms in IEEE 24 bus systems.The proposed method illustrates the effectiveness of utilizing DE-ZOA algorithm to find optimal solution for the ACTEP problem.