Publication: Reliability analysis of power system using sequential monte carlo simulation
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Date
2024-08
Authors
Muhammad Azri bin Ramly
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Abstract
This thesis presents a study on the reliability of power systems using the Sequential Monte Carlo (SMC) simulation method. Traditional methods often cannot
capture the complex and interconnected nature of power system components. This research uses the SMC simulation approach to model the random behavior of power systems over time. The study uses the IEEE Reliability Test System (RTS) as the benchmark for evaluating power system reliability. The IEEE-RTS provides detailed data on generators, transformers, transmission lines, and loads, along with their failure rates and probabilities. Using Monte Carlo sampling techniques, random samples are generated to simulate events like component failures, outages, and repairs. The simulation moves forward in time, simulating events in order and assessing their impact on system reliability. Various reliability metrics, including system reliability indices and loss of load probability, are calculated to evaluate power system performance. The results of this research provide useful insights for improving power system reliability and show that the SMC simulation approach offers a more detailed and flexible analysis of power system reliability.