Application of Genetic Algorithms to the Optimal Design of Power
Distribution Systems.

			(Abstract)

This PhD thesis presents the application of an evolutionary algorithm
(genetic algorithm), for finding out the best power distribution network
reliability while simultaneously minimizing the system expansion costs.
A non-linear mixed integer optimization model, achieving the optimal
sizing and location of future feeders (reserve feeders and operation
feeders) and substations, has been used. The proposed methodology has
been tested for distribution systems with dimensions that are
significantly larger than the ones frequently found in the papers about
this issue. The suitable curve of nondominated solutions, composed of a
high number of solutions, allows the planner to select a solution of the
multiobjective optimal design. Furthermore, this methodology is general
since it is suitable for the multiobjective optimization of n objectives
simultaneously. The model and the algorithm have been applied
intensively to real life power systems showing its potential of
applicability to large power distribution networks in practice.