Possibilistic model based on fuzzy sets for the multiobjective optimal planning of electric power distribution networks

This paper presents a new possibilistic (fuzzy) model for the multiobjective optimal planning of power distribution networks that finds out the nondominated multiobjective solutions corresponding to the simultaneous optimization of the fuzzy economic cost, level of fuzzy reliability, and exposure (optimization of robustness) of such networks, using an original and powerful meta-heuristic algorithm based on Tabu Search. This model determines the optimal location and size of the future feeders and substations in distribution networks with dimensions significantly larger than the ones usually presented in papers on the matter. The model also allows to determine the optimal reserve feeders (location and size) that provide the best distribution network reliability at the lowest cost for a given level of robustness (exposure). The model and the algorithm have been intensively tested in real distribution networks, which proves their practical application to large power distribution systems.