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The Transmission Expansion Planning (TEP) is still a highly complex, combinatorial, non-linear and non-convex problem, where more accurate models and more efficient optimization tools are needed. The purpose of this work is to solve the static Transmission Expansion Planning (TEP) problem through the Biogeography Based Optimization (BBO) technique using an AC model, for the simultaneous expansion...
We review alternative solutions for optical fronthauling in next generation fixed-mobile converged architectures that try to solve the problems related to the extremely high bit rates required by current fronthauling implementations based on the so-called digitized Radio over Fiber (as for the CPRI or OBSAI standards). In particular, we present our most recent results on Digital Signal Processing...
The Transmission Expansion Planning (TEP) problem is not a new issue, however, most research works presented so far use DC modeling, which can lead to very unrealistic transmission expansion plans. In order to deal with this problem, the use of the AC network model has been proposed recently by very few research works. Solving the TEP using the AC model is an extremely difficult task to deal with...
It is well known that the Transmission Expansion Planning (TEP) is a formidable combinatorial problem. Therefore more optimization techniques are needed to solve it in an efficient way. In this work the performance analysis of some Particle Swarm Optimization (PSO) versions to solve the Static Transmission Expansion Planning problem using the DC network model is carried out. The well-known Garver,...
It is well known that the Transmission Expansion Planning (TEP) is a formidable combinatorial problem; therefore more optimization techniques are needed to solve it in an efficient way. In this work it is proposed a parallel implementation of the Local Particle Swarm Optimization (LPSO) version to solve the Static Transmission Expansion Planning problem using the DC network model. The well-known Garver...
The Transmission Expansion Planning (TEP) problem is considered a very complex problem due to its combinatorial and nonconvex features. Some analytical and meta-heuristic methods have been proposed to tackle it, however, it is recognized that new efficient optimization tools are still needed. Particle Swarm Optimization has been an evolving research area in the last ten years and many interesting...
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