Biblio

The restoration of power distribution systems has a crucial role in the electric utility environment, taking into account both the pressure experienced by the operators that must choose the corrective actions to be followed in emergency restoration plans and the goals imposed by the regulatory agencies. In this sense, decision-aiding systems and self-healing networks may be good alternatives since they either perform an automated analysis of the situation, providing consistent and high-quality restoration plans, or even directly perform the restoration fast and automatically in both cases reducing the impacts caused by network disturbances. This work proposes a new restoration strategy which is novel in the sense it deals with the problem from the operator viewpoint, without simplifications that are used in most literature works. In this proposal, a permutation based genetic algorithm is employed to restore the maximum amount of loads, in real time, without depending on a priori knowledge of the location of the fault. To validate the proposed methodology two large real systems were tested: one with 2 substations, 5 feeders, 703 buses, and 132 switches, and; the other with 3 substations, 7 feeders, 21,633 buses, and 2,808 switches. These networks were tested considering situations of single and multiple failures. The results obtained were achieved with very low processing time (of the order of ten seconds), while compliance with all operational requirements was ensured.