Reliability Assessment of a Proposed Wind Farm Using Monte Carlo Simulation: A Case Study of Zuwara, Libya

This study assesses the reliability of a proposed 50 MW wind farm in Zuwara, Libya, under variable wind conditions. A 10-year wind dataset comprising 3,652 daily observations was obtained from the NASA POWER database to characterize the site wind resource. Several probability distributions were evaluated, and the Johnson SB distribution was selected based on goodness-of-fit using the Kolmogorov–Smirnov (KS) test. The resulting wind-speed model was integrated with the power characteristics of a 50-turbine wind farm, each rated at 1 MW. Monte Carlo simulation was applied to represent wind-generation variability and evaluate its effect on generation adequacy under different demand levels. Using the Resistance–Load (R–L) approach, loss-of-load conditions were identified when available wind generation was insufficient to meet the considered demand. The results show that the estimated failure probability was approximately 88.39% for a 32-MW demand and 92.99% for a 38-MW demand. Increasing the number of simulation trials reduced the statistical error and improved the stability of the estimates. The findings demonstrate the strong influence of wind variability and demand level on the reliability contribution of the proposed wind farm and highlight the need for complementary resources to improve supply adequacy.