Optimal static and dynamic transmission network expansion planning

In this paper, a novel approach is proposed to solve the problem of static and dynamic Transmission expansion planning (TEP) in electrical power systems. The proposed method is the execution of an Adaptive salp swarm optimization algorithm (ASSO). The ASSO is a meta-heuristic algorithm, which depends on the swarming behavior and population of salps. In the proposed approach, ASSO is the charge of acquiring the best candidate solution for the expansion planning and locate the optimal solution for both the static and the dynamic transmission network expansion in perspective of the minimum error objective function. The objective is formulated to minimize the cost of investment in transmission systems by satisfying the constraints such as active power balance, expansion parameter, and load shedding restrictions. The proposed ASSO technique ensures the system with less complexity, reduced computational time and hence the efficiency of the system is raised. Finally, the proposed model is executed in MATLAB/Simulink working stage and the execution is compared with the existing techniques.