Stochastic Process for the Availability Assessment of Single-Feeder Industrial Energy System Sections

Given the high interruption costs of industrial processes, dependent on the cause, duration, and time, accurate availability assessment of the industrial energy systems (IES) supplying those processes is crucial in order to avoid unnecessary investments or indicate necessary improvements. A method is presented to sectionalize an IES based on its radial topology and recoverability options. Additionally, this paper introduces a novel nonrenewal stochastic process able to compute the (un)availability of single-feeder sections with respect to cause, duration, and time, taking into account competing risks, general transition rates, and both minimal and perfect corrective maintenance. An accompanying solution strategy is developed, which allows decoupling of the very diverse time constants. Finally, a numerical illustration is provided validating the proposed approach against the Markov and semi-Markov processes under their respective assumptions and illustrating the possible errors when modeling the problem using the aforementioned stochastic processes.