Discrete-Time Approximate Optimization Algorithm for Intelligent Line Selection System

Abstract

In this paper, the discrete-time optimization problem for transmission line planning for power systems is studied, in which the local cost function is considered. Firstly, a global cost function is constructed by using penalty function method. Secondly, for the optimization problem of intelligent line selection system, a discrete-time optimization algorithm is proposed. In the optimization algorithm design, the gradient of approximate cost function is used. In the proposed algorithm, the global optimal advantage of each sub-stage is selected, and the optimal advantage can be adjusted by penalty parameters. Compared with the traditional optimization algorithm, the convergence time and accuracy are improved. Finally, the example simulation results verify the effectiveness and superiority of the proposed discrete-time optimization algorithm.