Abstract (EN):
Transmission Expansion Planning (TEP) is an
optimization problem that has a non-convex and combinatorial
search space so that several solution algorithms may converge to
local optima. Therefore, many works have been proposed to solve
the TEP problem considering its relaxation or reducing its search
space. In any case, relaxation and reduction approaches should
not compromise the quality of the final solution. This paper aims
at analyzing the performance of a search space technique using a
Constructive Heuristic Algorithm (CHA) admitting that the TEP
problem is then solved using a Discreet Evolutionary Particle
Swarm Optimization (DEPSO). On one hand the reduction
quality is performed by analyzing whether the optimal expansion
routes are included in the CHA constrained set and, on the other
hand, the relaxation quality of the DC model is analyzed by
checking if the optimal solution obtained with it violates any
constraint using the AC model. The simulations were performed
using three different test systems. The results suggest that the
proposed CHA provides very good results in reducing the TEP
search space and that the adoption of the DC model originates
several violations if the full AC model is used to model the
operation of the power system.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
5
License type: