A Combined Stochastic Approach for Enhancing Power Supply Reliability and Availability of Critical Users, Using Petri Nets Model, Monte Carlo Simulation and Fuzzy Logic

Abstract

Power supply interruptions and outages constitute a highly significant concern for industrial and critical users, especially in the oil and gas sector, where any interruption means a substantial economic impact. This study aims to assess the reliability and the availability of power supply within an oil and gas company located in southern Algeria, which is a region known by its harsh and severe environmental conditions such as high temperatures, strong winds, and geographical constraints. This work focused on evaluating these constraints and their impact on energy availability using dynamic reliability approach: Petri nets model PNM and Monte Carlo simulation MCS coupled with fuzzy logic to assess dynamic variables. Three different power networks were evaluated, and the results indicated that environmental constraints have a significant impact on power supply availability resulting from the occurrence of common cause failures, delays time, and the probability of failure on demand. These results emphasize the necessity of dynamic evaluation of power networks rather than relying solely on static data, which may lead to incorrect decisions regarding the choice of backup energy sources.