A new approach for reliability-centered maintenance programs in electric power distribution systems based on a multiobjective genetic algorithm

• A novel multiobjective methodology for optimization of preventive maintenance programs in electric power distribution systems is proposed.
• The mathematical model of dynamic programming comprises the philosophy of reliability centered maintenance (RCM).
• The reliability index of each equipment is considered as a predictive index.
• Fuzzy logic inference system is used to update dynamically the reliability index of equipment in the time horizon.
• We propose a Nondominated Sorting Genetic Algorithm to solve the multiobjective optimization problem.

This paper proposes a multiobjective model to solve the mathematical problem of optimizing reliability-centered maintenance planning of an electric power distribution system (EPDS). The main goal is to minimize the preventive maintenance costs while maximizing the index of reliability of the whole system. In the proposed model, the limits of the indices, such as SAIDI and SAIFI, are considered as constraints of the maintenance programs. The reliability indices of the EPDS components are evaluated and updated by a fuzzy inference system. A NSGA-II algorithm was proposed to solve the multiobjective model that provides an optimized Pareto frontier. The results obtained from applying the proposed methodology to a system with three feeders and 733 components are presented, showing its robustness and quality for maintenance planning in EPDS.