solution of the electric power transmission-network expansion planning problem by means of a genetic algorithm and linear and non-linear programming
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In this paper, an efficient approach is proposed for the reduction of the computational effort associated to the solution of the electric power transmission-network expansion planning problem. This approach makes use of a non-linear interior-point method to start the population of a genetic algorithm that iteratively solves the problem of investment. From the beginning of the solution, the generated configurations are of high quality and are located at strategic points of the solution space so that they can evolve towards optimal regions. The investment plan for the genetic algorithm was evaluated on a transmission system through a linear interior-point method. The proposed approach was tested on 6 and 24-bus IEEE systems and on the South Brazilian 46-bus system. An excellent performance of the genetic algorithm was obtained for these systems and a lesser computational effort was required for the solution of the problem.
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