Abstract
In this study, levelized cost of energy (LCOE) was assessed considering uncertainty in downtime and repair cost by using NEDO database. Firstly, NEDO database was implemented and validated by using METI database, which enabled reliability analysis in Japan. Then, probabilistic models of downtime and repair cost were built by using beta function for each downtime bin. The correlation between downtime and repair cost were modeled by using t copula. Predicted downtime and repair cost showed good agreement with observation in NEDO data. Finally, LCOE was evaluated by using the proposed downtime and repair cost models and cost reduction scenario was investigated to clarify the cost reduction effect of smart maintenance.
