Author Description

Due to the accelerated growth of electricity demand, the scarcity of primary resources to produce electricity, and technological advances in recent years, electricity companies must face and solve these challenges in the best possible way, and for that, the Transmission Network Expansion Planning (TNEP) plays a crucial role, since the decisions taken in long term planning determine the optimal form of expansion of the networks, to respond to these needs of electricity demands. On the other hand, there is also the tendency to leave the TNEP problem more efficient, robust, and closer to to what happens in real electrical networks. For these reasons, this article proposes a methodology to solve the TNEP problem considering active power losses. On the other hand, is developed a modeling and solution approach to the static and multistage transmission network expansion planning problem considering series capacitive compensation and active power losses. The transmission network expansion planning is formulated as a mixed integer nonlinear programming problem and solved through a highly efficient genetic algorithm. Furthermore, the Villasana Garver's constructive heuristic algorithm is implemented to render the configurations of the genetic algorithm feasible. The installation of series capacitive compensation devices is carried out with the aim of modifying the reactance of the original circuit. The linearization of active power losses is done through piecewise linear functions.