Risk based maintenance optimization of overhead distribution networks utilizing priority based dynamic programming

This paper presents a priority based dynamic programming approach for long term maintenance scheduling of overhead distribution networks. The proposed approach is based on risk management approach and utilizes the model of decoupled risk factors. Two heuristic factors are defined and utilized in order to establish a maintenance priority list and to curtail the dynamic programming search space. The proposed methodology yields a significant computational saving compare to the previously reported dynamic programming. Risk management approach enables the asset managers to consider the actual condition of electrical equipments and expected consequence of their failures. Furthermore, the decoupled risk strategy in conjunction with the piecewise modeling of failure rate establishes a precise description of time-dependent deterioration failure rate and provides the ability to determine the most cost-effective maintenance scenario. The proposed approach is applied to the RBTS distribution feeders and a typical real size case study. The results presented show the accuracy and efficiency of the proposed approach.