Abstract
In this work, the planning problem of primary distribution networks is formulated as a multi-objective mixed-integer non-linear programming model (MINLP). The objective functions of this model are the expansion and operation investment costs of primary distribution networks as well as the system's reliability costs in the contingency events. The reliability costs are obtained by means of calculating the non-supplied energy because of the repairing and switching operations in the distribution network carried out to isolate and to redistribute loads in the affected sections by permanent faults. In order to solve the expansion problem of the primary network a Multi-objective Reactive Tabu Search algorithm (MO-RTS) is proposed. The concepts of dominance are used to obtain Pareto's optimal frontier in the MO-RTS. The problem of placement of sectionalising switches (automatic or manual) to restore the distribution network and to reduce non-supplied energy costs when permanent faults occur in the network is solved simultaneously with the network expansion planning problem by means of a dedicated genetic algorithm. For testing, the proposed methodology is used as a primary power distribution system, with 180 points of consumption, where 49 already exist and 131 can be added to the system during the planning process.
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