A Heuristic Approach for the Optimization of Maintenance Task Plans in Electric Power Distribution Systems With Resource Constraints

Abstract

In this study, we present a new approach for the optimized scheduling of maintenance tasks in electric power distribution networks based on a classic optimization technique. The original mixed-integer non-linear programming model is linearized using the piecewise linearization technique, adopting a classical pseudo-dynamic convex optimization approach as a solution technique for horizon planning. The objective is to determine an optimized maintenance plan over a pre-established planning horizon that can improve the reliability of the system, considering financial resource constraints, allocation of maintenance activities in de-energized networks among specialized crews, and restricting the cost of unsupplied energy resulting from the execution of maintenance tasks on de-energized lines. The mixed-integer binary linear programming mathematical model was implemented in AMPL language and solved using the CPLEX solver. The computational implementation of the proposed methodology was tested on a real network of 435 nodes, distributed across 56 sections. The results obtained demonstrate an improvement in the reliability of equipment installed in the system sections over the period, such as the prioritization of maintenance task assignments in the sections that contribute the most to the reliability of the network and continuity indicators, in addition to the efficient direction of maintenance activities for equipment with higher failure rates and lower intervention costs. The results obtained by the computational implementation of the proposed methodology are presented and discussed, demonstrating the efficiency and application of the proposed mathematical model and methodology to simulate real systems.