Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks

This paper addresses the optimal power flow problem in direct current (DC) networks employing a master–slave solution methodology that combines an optimization algorithm based on multiverse theory (master stage) and numerical method of successive approximation (slave stage). The master stage proposes levels to be injected by each distributed generator DC network, slave evaluates impact configuration (proposed objective function set constraints compose problem. In this study, is reduction electrical losses associated with energy transmission. addition, are global balance, nodal voltage limits, maximum level penetration generators. order validate robustness repeatability solution, study used four other methods have been reported specialized literature solve addressed here: ant lion optimization, particle swarm continuous genetic algorithm, black hole algorithm. All them employed load 21- 69-node test systems were for purpose, enabling generators inject 20%, 40%, 60% provided slack node scenario without generation. results revealed optimizer offers best quality different sizes several