Abstract
Service restoration in contingency situations is one of the most critical problems in the context of distribution system operation. It is a problem with multiple objectives and multiple constraints whose solution must be gotten as soon as possible. Besides, due to the existence of customers with higher priority of supply (e.g., big industries and hospitals), it is necessary to prioritize service restoration to these loads. However, it is important to highlight that these priority customers have different priority levels, that also must be considered during the determination of a feasible service restoration plan. In this paper, a methodology based on multi-objective evolutionary algorithm is proposed for solving service restoration problem in large-scale distribution system taking into account the existence of three levels of priority customers. Simulations results have shown the proposed methodology is able to find suitable service restoration plans for large-scale real distribution systems (from 3,860 to 30,880 buses) with relatively soft computing without requiring any network simplification.
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