Realistic Availability Assessment of Energy System Behavior Patterns by Monte Carlo Method

Due to the current financial constraints in the energy industry, investors need realistic risk evaluation and economic analysis in energy investment projects. On the other hand, energy system operators are continuously facing a wide range of challenges when dealing with asset management practices of the system components. In this paper, a novel method is proposed for the availability assessment of energy systems. This method provides an opportunity to predict system real behavior patterns in simulated time. According to the designed procedure, two new parameters for availability assessment are defined as the Failure Moment (FM) and the Repair Moment (RM). FM and RM of the components are estimated by the Monte Carlo method based on the time-varying failure rate and repair rate, respectively. This process is continued for all selected components in the system lifetime. As a common practice for demonstrating novel methodologies, the proposed method of this study is applied to the Combined Cycle Gas Turbine Power Plants. The results show that realistic availability evaluation for energy systems with the Monte Carlo method can cause a 4.4% reduction in nominal fuel consumption (16.79 kg/s as an average fuel flow rate vs. 17.562 kg/s as nominal amount) and a 5.05% reduction in nominal power generation. Therefore, this consideration makes the investment analysis more accurate and the decision to invest more interesting.